Scalable Multi-Objective Reinforcement Learning with Fairness Guarantees using Lorenz Dominance


Scalable Multi-Robot Informative Path Planning for Target Mapping via Deep Reinforcement Learning


Scalable Multi-Stage Influence Function for Large Language Models via Eigenvalue-Corrected Kronecker-Factored Parameterization


Scalable Multi-Temporal Remote Sensing Change Data Generation via Simulating Stochastic Change Process


Scalable Multi-agent Reinforcement Learning Algorithm for Wireless Networks


Scalable Multi-modal Model Predictive Control via Duality-based Interaction Predictions


Scalable Multi-node Fast Fourier Transform on GPUs


Scalable Multi-view Clustering with Graph Filtering


Scalable Multiagent Coordination with Distributed Online Open Loop Planning


Scalable Multiple Network Inference with the Joint Graphical Horseshoe


Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity


Scalable Neural Network Training over Distributed Graphs


Scalable Neural Quantum State based Kernel Polynomial Method for Optical Properties from the First Principle


Scalable Neural Video Representations with Learnable Positional Features


Scalable Neural-Probabilistic Answer Set Programming


Scalable Non-Equivariant 3D Molecule Generation via Rotational Alignment


Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap


Scalable Offline Reinforcement Learning for Mean Field Games


Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation


Scalable Online Betweenness Centrality in Evolving Graphs


Scalable Online Exploration via Coverability


Scalable Online Recurrent Learning Using Columnar Neural Networks


Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey


Scalable Optimization for Wind Farm Control using Coordination Graphs


Scalable Parallel Algorithm for Graph Neural Network Interatomic Potentials in Molecular Dynamics Simulations


Scalable Parameter and Memory Efficient Pretraining for LLM: Recent Algorithmic Advances and Benchmarking


Scalable Pareto Front Approximation for Deep Multi-Objective Learning


Scalable Penalized Regression for Noise Detection in Learning with Noisy Labels


Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks


Scalable Performance Analysis for Vision-Language Models


Scalable Polyhedral Verification of Recurrent Neural Networks


Scalable Power Control/Beamforming in Heterogeneous Wireless Networks with Graph Neural Networks


Scalable Probabilistic Matrix Factorization with Graph-Based Priors


Scalable Program Clone Search Through Spectral Analysis


Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory


Scalable Proof Producing Multi-Threaded SAT Solving with Gimsatul through Sharing instead of Copying Clauses


Scalable Quantum Neural Networks for Classification


Scalable Quantum Tomography with Fidelity Estimation


Scalable Randomized Kernel Methods for Multiview Data Integration and Prediction


Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks


Scalable Real2Sim: Physics-Aware Asset Generation Via Robotic Pick-and-Place Setups


Scalable Recommendation of Wikipedia Articles to Editors Using Representation Learning


Scalable Regularised Joint Mixture Models


Scalable Reinforcement Learning Policies for Multi-Agent Control


Scalable Relational Query Processing on Big Matrix Data


Scalable Resource Management for Dynamic MEC: An Unsupervised Link-Output Graph Neural Network Approach


Scalable Ride-Sourcing Vehicle Rebalancing with Service Accessibility Guarantee: A Constrained Mean-Field Reinforcement Learning Approach


Scalable Rule Lists Learning with Sampling


Scalable Safe Multi-Agent Reinforcement Learning for Multi-Agent System


Scalable Sampling for High Utility Patterns


Scalable Sampling for Nonsymmetric Determinantal Point Processes


Scalable Sampling of Truncated Multivariate Normals Using Sequential Nearest-Neighbor Approximation


Scalable Scalar-on-Image Cortical Surface Regression with a Relaxed-Thresholded Gaussian Process Prior


Scalable Second Order Optimization for Deep Learning


Scalable Semi-Modular Inference with Variational Meta-Posteriors


Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation


Scalable Signature Kernel Computations for Long Time Series via Local Neumann Series Expansions


Scalable Simulation of Fermionic Encoding Performance on Noisy Quantum Computers


Scalable Spatio-Temporal Smoothing via Hierarchical Sparse Cholesky Decomposition


Scalable Spatiotemporal Graph Neural Networks


Scalable Spatiotemporal Prediction with Bayesian Neural Fields


Scalable Spectral Clustering Using Random Binning Features


Scalable Spectral Clustering with Group Fairness Constraints


Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference


Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal Metrics


Scalable Structure Learning for Sparse Context-Specific Systems


Scalable Subset Selection in Linear Mixed Models


Scalable Subspace Methods for Derivative-Free Nonlinear Least-Squares Optimization


Scalable Temporal Anomaly Causality Discovery in Large Systems: Achieving Computational Efficiency with Binary Anomaly Flag Data


Scalable Temporal Motif Densest Subnetwork Discovery


Scalable Traffic Engineering for Higher Throughput in Heavily-loaded Software Defined Networks


Scalable Training of Neural Network Potentials for Complex Interfaces Through Data Augmentation


Scalable Transceiver Design for Multi-User Communication in FDD Massive MIMO Systems via Deep Learning


Scalable Transfer Evolutionary Optimization: Coping with Big Task Instances


Scalable Transformer for High Dimensional Multivariate Time Series Forecasting


Scalable Transformer for PDE Surrogate Modeling


Scalable Tree-based Register Automata Learning


Scalable Unbalanced Optimal Transport using Generative Adversarial Networks


Scalable Unbalanced Sobolev Transport for Measures on a Graph


Scalable Uncertainty Quantification for Deep Operator Networks using Randomized Priors


Scalable Variational Causal Discovery Unconstrained by Acyclicity


Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition


Scalable Verification of GNN-based Job Schedulers


Scalable Vision Transformers with Hierarchical Pooling


Scalable Vision-Based 3D Object Detection and Monocular Depth Estimation for Autonomous Driving


Scalable Volt-VAR Optimization using RLlib-IMPALA Framework: A Reinforcement Learning Approach


Scalable Wavelength Arbitration for Microring-based DWDM Transceivers


Scalable Weibull Graph Attention Autoencoder for Modeling Document Networks


Scalable algorithms for semiparametric accelerated failure time models in high dimensions


Scalable and Accurate Application-Level Crash-Consistency Testing via Representative Testing


Scalable and Accurate Dialogue State Tracking via Hierarchical Sequence Generation


Scalable and Accurate Test Case Prioritization in Continuous Integration Contexts


Scalable and Accurate Variational Bayes for High-Dimensional Binary Regression Models


Scalable and Certifiable Graph Unlearning: Overcoming the Approximation Error Barrier


Scalable and Effective Arithmetic Tree Generation for Adder and Multiplier Designs


Scalable and Effective Generative Information Retrieval


Scalable and Efficient Continual Learning from Demonstration via a Hypernetwork-generated Stable Dynamics Model


Scalable and Efficient Functional Map Computations on Dense Meshes


Scalable and Efficient Hierarchical Visual Topological Mapping


Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data


Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency


Scalable and Flexible Classical Shadow Tomography with Tensor Networks


Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features


Scalable and Order-robust Continual Learning with Additive Parameter Decomposition


Scalable and Provably Accurate Algorithms for Differentially Private Distributed Decision Tree Learning


Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems


Scalable and Robust Physics-Informed Graph Neural Networks for Water Distribution Systems


Scalable and Secure Row-Swap: Efficient and Safe Row Hammer Mitigation in Memory Systems


Scalable and optimal Bayesian inference for sparse covariance matrices via screened beta-mixture prior


Scalable and robust regression models for continuous proportional data


Scalable approach to many-body localization via quantum data


Scalable calibration of individual-based epidemic models through categorical approximations


Scalable communication for high-order stencil computations using CUDA-aware MPI


Scalable computation of predictive probabilities in probit models with Gaussian process priors


Scalable couplings for the random walk Metropolis algorithm


Scalable deeper graph neural networks for high-performance materials property prediction


Scalable estimation and inference for censored quantile regression process


Scalable evaluation of quantum-circuit error loss using Clifford sampling


Scalable expectation propagation for generalized linear models


Scalable hierarchical BayeSN inference: Investigating dependence of SN Ia host galaxy dust properties on stellar mass and redshift


Scalable high-resolution forecasting of sparse spatiotemporal events with kernel methods: a winning solution to the NIJ "Real-Time Crime Forecasting Challenge"


Scalable inference of topic evolution via models for latent geometric structures


Scalable k-Means Clustering for Large k via Seeded Approximate Nearest-Neighbor Search


Scalable kernel balancing weights in a nationwide observational study of hospital profit status and heart attack outcomes


Scalable knowledge base completion with superposition memories


Scalable learning of potentials to predict time-dependent Hartree-Fock dynamics


Scalable magnetic resonance fingerprinting: Incremental inference of high dimensional elliptical mixtures from large data volumes


Scalable marginalization of correlated latent variables with applications to learning particle interaction kernels


Scalable measures of magic resource for quantum computers


Scalable method for Bayesian experimental design without integrating over posterior distribution


Scalable methods for nonnegative matrix factorizations of near-separable tall-and-skinny matrices


Scalable molecular simulation of electrolyte solutions with quantum chemical accuracy


Scalable multi-class sampling via filtered sliced optimal transport


Scalable multicomponent spectral analysis for high-throughput data annotation


Scalable penalized spatiotemporal land-use regression for ground-level nitrogen dioxide


Scalable physical source-to-field inference with hypernetworks


Scalable random number generation for truncated log-concave distributions


Scalable semi-supervised dimensionality reduction with GPU-accelerated EmbedSOM


Scalable sim-to-real transfer of soft robot designs


Scalable simulation-based inference for implicitly defined models using a metamodel for Monte Carlo log-likelihood estimator


Scalable stellar evolution forecasting: Deep learning emulation vs. hierarchical nearest neighbor interpolation


Scalable tensor methods for nonuniform hypergraphs


Scalable unsupervised feature selection via weight stability


Scalable variable selection for two-view learning tasks with projection operators


Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data


Scalable, Detailed and Mask-Free Universal Photometric Stereo


Scalable, Training-Free Visual Language Robotics: A Modular Multi-Model Framework for Consumer-Grade GPUs


Scalable-Complexity Steered Response Power Mapping based on Low-Rank and Sparse Interpolation


ScalableMap: Scalable Map Learning for Online Long-Range Vectorized HD Map Construction


Scalably learning quantum many-body Hamiltonians from dynamical data


Scalar Field Prediction on Meshes Using Interpolated Multi-Resolution Convolutional Neural Networks


Scalar Product Lattice Computation for Efficient Privacy-preserving Systems


Scalar Reduction of a Neural Field Model with Spike Frequency Adaptation


Scalar field Restricted Boltzmann Machine as an ultraviolet regulator


Scalar is Not Enough: Vectorization-based Unbiased Learning to Rank


Scalar on time-by-distribution regression and its application for modelling associations between daily-living physical activity and cognitive functions in Alzheimer's Disease


Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery


Scale Effects in Ridesplitting: A Case Study of the City of Chicago


Scale Efficient Training for Large Datasets


Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers


Scale Equalization for Multi-Level Feature Fusion


Scale Equivariance Improves Siamese Tracking


Scale Federated Learning for Label Set Mismatch in Medical Image Classification


Scale Guided Hypernetwork for Blind Super-Resolution Image Quality Assessment


Scale Mixtures of Neural Network Gaussian Processes


Scale Propagation Network for Generalizable Depth Completion


Scale Steerable Filters for Locally Scale-Invariant Convolutional Neural Networks


Scale dependant layer for self-supervised nuclei encoding


Scale invariant robot behavior with fractals


Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution


Scale-Adaptive Neural Dense Features: Learning via Hierarchical Context Aggregation


Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection


Scale-Aware Dynamic Network for Continuous-Scale Super-Resolution


Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting


Scale-Distribution Decoupling: Enabling Stable and Effective Training of Large Language Models


Scale-Equalizing Pyramid Convolution for Object Detection


Scale-Equivariant Deep Learning for 3D Data


Scale-Equivariant Imaging: Self-Supervised Learning for Image Super-Resolution and Deblurring


Scale-Free Image Keypoints Using Differentiable Persistent Homology


Scale-Invariant Fast Functional Registration


Scale-Invariant Monocular Depth Estimation via SSI Depth


Scale-Invariant Structure Saliency Selection for Fast Image Fusion


Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning


Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction


Scale-Preserving Automatic Concept Extraction (SPACE)


Scale-Score: Food Label to Support Nutritious and Sustainable Online Grocery Shopping


Scale-Separated Dynamic Mode Decomposition and Ionospheric Forecasting


Scale-Translation Equivariant Network for Oceanic Internal Solitary Wave Localization


Scale-aware Automatic Augmentation for Object Detection


Scale-aware Test-time Click Adaptation for Pulmonary Nodule and Mass Segmentation


Scale-bridging within a complex model hierarchy for investigation of a metal-fueled circular energy economy by use of Bayesian model calibration with model error quantification


Scale-constrained Unsupervised Evaluation Method for Multi-scale Image Segmentation


Scale-dependent measure of network centrality from diffusion dynamics


Scale-invariant Learning by Physics Inversion


Scale-invariant biomarker discovery in urine and plasma metabolite fingerprints


Scale-invariant representation of machine learning


Scale-recurrent Network for Deep Image Deblurring


Scale-tailored localization and its observation in non-Hermitian electrical circuits


Scale-up Unlearnable Examples Learning with High-Performance Computing


Scale-variant topological information for characterizing complex networks


Scale-wise Convolution for Image Restoration


ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models


ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth Estimation


ScaleDreamer: Scalable Text-to-3D Synthesis with Asynchronous Score Distillation


ScaleFace: Uncertainty-aware Deep Metric Learning


ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation


ScaleFusionNet: Transformer-Guided Multi-Scale Feature Fusion for Skin Lesion Segmentation


ScaleHLS: A New Scalable High-Level Synthesis Framework on Multi-Level Intermediate Representation


ScaleKD: Strong Vision Transformers Could Be Excellent Teachers


ScaleLSD: Scalable Deep Line Segment Detection Streamlined


ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding


ScaleLong: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection


ScaleMAI: Accelerating the Development of Trusted Datasets and AI Models


ScaleNet: A Shallow Architecture for Scale Estimation


ScaleNet: Searching for the Model to Scale


Scaled Supervision is an Implicit Lipschitz Regularizer


Scaled Vecchia approximation for fast computer-model emulation


Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting


ScalerEval: Automated and Consistent Evaluation Testbed for Auto-scalers in Microservices


Scalify: scale propagation for efficient low-precision LLM training


Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning


Scaling Adversarial Training to Large Perturbation Bounds


Scaling Attention to Very Long Sequences in Linear Time with Wavelet-Enhanced Random Spectral Attention (WERSA)


Scaling Back-Translation with Domain Text Generation for Sign Language Gloss Translation


Scaling Backwards: Minimal Synthetic Pre-training?


Scaling Bayesian Probabilistic Record Linkage with Post-Hoc Blocking: An Application to the California Great Registers


Scaling Behavior of Machine Translation with Large Language Models under Prompt Injection Attacks


Scaling Blockchain Consensus via a Robust Shared Mempool


Scaling Capability in Token Space: An Analysis of Large Vision Language Model


Scaling CheckMate for Game-Theoretic Security


Scaling Compute Is Not All You Need for Adversarial Robustness


Scaling Data Diversity for Fine-Tuning Language Models in Human Alignment


Scaling Data Generation in Vision-and-Language Navigation


Scaling Data-Constrained Language Models


Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup


Scaling Diffusion Language Models via Adaptation from Autoregressive Models


Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion


Scaling Diffusion Transformers to 16 Billion Parameters


Scaling Down Deep Learning with MNIST-1D


Scaling Down Text Encoders of Text-to-Image Diffusion Models


Scaling Down to Scale Up: A Cost-Benefit Analysis of Replacing OpenAI's LLM with Open Source SLMs in Production


Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning


Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models


Scaling Effects of Transistor Leakage Current and IR Drop on 1T1R Memory Arrays


Scaling Efficient Masked Image Modeling on Large Remote Sensing Dataset


Scaling Expert Language Models with Unsupervised Domain Discovery


Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration


Scaling Federated Learning Solutions with Kubernetes for Synthesizing Histopathology Images


Scaling Graph Convolutions for Mobile Vision


Scaling Image Tokenizers with Grouped Spherical Quantization


Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension


Scaling K2. II. Assembly of a Fully Automated C5 Planet Candidate Catalog Using EDI-Vetter


Scaling Knowledge Graphs for Automating AI of Digital Twins


Scaling LLM Inference with Optimized Sample Compute Allocation


Scaling Language-Image Pre-training via Masking


Scaling Large Motion Models with Million-Level Human Motions


Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations


Scaling Laws for Data Filtering -- Data Curation cannot be Compute Agnostic


Scaling Laws for Imitation Learning in Single-Agent Games


Scaling Laws for Linear Complexity Language Models


Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets


Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream


Scaling Laws for a Multi-Agent Reinforcement Learning Model


Scaling Laws for the Value of Individual Data Points in Machine Learning


Scaling Laws of RoPE-based Extrapolation


Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies


Scaling Learning based Policy Optimization for Temporal Logic Tasks by Controller Network Dropout


Scaling Manipulation Learning with Visual Kinematic Chain Prediction


Scaling Mesh Generation via Compressive Tokenization


Scaling Model Checking for DNN Analysis via State-Space Reduction and Input Segmentation (Extended Version)


Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing


Scaling Multi-Camera 3D Object Detection through Weak-to-Strong Eliciting


Scaling Multi-Document Event Summarization: Evaluating Compression vs. Full-Text Approaches


Scaling Multi-Objective Security Games Provably via Space Discretization Based Evolutionary Search


Scaling Neural Program Synthesis with Distribution-based Search


Scaling Neural Tangent Kernels via Sketching and Random Features


Scaling Novel Object Detection with Weakly Supervised Detection Transformers


Scaling Object Detection by Transferring Classification Weights


Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining


Scaling Open-Vocabulary Action Detection


Scaling Open-Vocabulary Image Segmentation with Image-Level Labels


Scaling Out-of-Distribution Detection for Real-World Settings


Scaling Package Queries to a Billion Tuples via Hierarchical Partitioning and Customized Optimization


Scaling Pareto-Efficient Decision Making Via Offline Multi-Objective RL


Scaling Particle Collision Data Analysis


Scaling Probabilistic Circuits via Data Partitioning


Scaling Properties of Deep Residual Networks


Scaling Reasoning can Improve Factuality in Large Language Models


Scaling Reasoning, Losing Control: Evaluating Instruction Following in Large Reasoning Models


Scaling Representation Learning from Ubiquitous ECG with State-Space Models


Scaling ResNets in the Large-depth Regime


Scaling Retrieval-Based Language Models with a Trillion-Token Datastore


Scaling Rich Style-Prompted Text-to-Speech Datasets


Scaling Safe Multi-Agent Control for Signal Temporal Logic Specifications


Scaling Semantic Segmentation Beyond 1K Classes on a Single GPU


Scaling Sentence Embeddings with Large Language Models


Scaling Sequential Recommendation Models with Transformers


Scaling Session-Based Transformer Recommendations using Optimized Negative Sampling and Loss Functions


Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization


Scaling Sparse and Dense Retrieval in Decoder-Only LLMs


Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training


Scaling Structure Aware Virtual Screening to Billions of Molecules with SPRINT


Scaling Supervised Local Learning with Augmented Auxiliary Networks


Scaling Symbolic Methods using Gradients for Neural Model Explanation


Scaling Synthetic Data Creation with 1,000,000,000 Personas


Scaling Synthetic Logical Reasoning Datasets with Context-Sensitive Declarative Grammars


Scaling Systematic Literature Reviews with Machine Learning Pipelines


Scaling Training Data with Lossy Image Compression


Scaling Transformers for Low-Bitrate High-Quality Speech Coding


Scaling Up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image Segmentation


Scaling Up Computer Vision Neural Networks Using Fast Fourier Transform


Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory


Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks


Scaling Up Exact Neural Network Compression by ReLU Stability


Scaling Up Graph Neural Networks Via Graph Coarsening


Scaling Up Hardware Accelerator Verification using A-QED with Functional Decomposition


Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models


Scaling Up Personalized Image Aesthetic Assessment via Task Vector Customization


Scaling Up Resonate-and-Fire Networks for Fast Deep Learning


Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data


Scaling Up Single Image Dehazing Algorithm by Cross-Data Vision Alignment for Richer Representation Learning and Beyond


Scaling Up and Distilling Down: Language-Guided Robot Skill Acquisition


Scaling Up: Revisiting Mining Android Sandboxes at Scale for Malware Classification


Scaling Video Analytics on Constrained Edge Nodes


Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation


Scaling While Privacy Preserving: A Comprehensive Synthetic Tabular Data Generation and Evaluation in Learning Analytics


Scaling a Variant Calling Genomics Pipeline with FaaS


Scaling and Masking: A New Paradigm of Data Sampling for Image and Video Quality Assessment


Scaling associative classification for very large datasets


Scaling field-theoretic simulation for multi-component mixtures with neural operators


Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement


Scaling in local to global condensation of wealth on sparse networks


Scaling laws for language encoding models in fMRI


Scaling laws for the geometry of an impact-induced magma ocean


Scaling may be all you need for achieving human-level object recognition capacity with human-like visual experience


Scaling of Class-wise Training Losses for Post-hoc Calibration


Scaling of hardware-compatible perturbative training algorithms


Scaling of neural-network quantum states for time evolution


Scaling on-chip photonic neural processors using arbitrarily programmable wave propagation


Scaling pattern mining through non-overlapping variable partitioning


Scaling physics-informed hard constraints with mixture-of-experts


Scaling priors in two dimensions for Intrinsic Gaussian MarkovRandom Fields


Scaling properties of exclusive vector meson production cross section from gluon saturation


Scaling properties of scale-free networks in degree-thresholding renormalization flows


Scaling structural learning with NO-BEARS to infer causal transcriptome networks


Scaling study of diffusion in dynamic crowded spaces


Scaling the Codebook Size of VQGAN to 100,000 with a Utilization Rate of 99%


Scaling the Indian Buffet Process via Submodular Maximization


Scaling the Wild: Decentralizing Hogwild!-style Shared-memory SGD


Scaling transformer neural networks for skillful and reliable medium-range weather forecasting


Scaling tunnelling noise in the fractional quantum Hall effect tells about renormalization and breakdown of chiral Luttinger liquid


Scaling up DNA digital data storage by efficiently predicting DNA hybridisation using deep learning


Scaling up Discovery of Latent Concepts in Deep NLP Models


Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing


Scaling up Masked Diffusion Models on Text


Scaling up Memory-Efficient Formal Verification Tools for Tree Ensembles


Scaling up Probabilistic PDE Simulators with Structured Volumetric Information


Scaling up Ranking under Constraints for Live Recommendations by Replacing Optimization with Prediction


Scaling up Search Engine Audits: Practical Insights for Algorithm Auditing


Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach


Scaling up ridge regression for brain encoding in a massive individual fMRI dataset


Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks


Scaling up the self-optimization model by means of on-the-fly computation of weights


Scaling up the transcorrelated density matrix renormalization group


Scaling-up Disentanglement for Image Translation


Scalpel: The Python Static Analysis Framework


ScamFerret: Detecting Scam Websites Autonomously with Large Language Models


Scampi: a robust approximate message-passing framework for compressive imaging


Scan-flood Fill(SCAFF): an Efficient Automatic Precise Region Filling Algorithm for Complicated Regions


Scan-specific Self-supervised Bayesian Deep Non-linear Inversion for Undersampled MRI Reconstruction


Scan-specific, Parameter-free Artifact Reduction in K-space (SPARK)


ScanBank: A Benchmark Dataset for Figure Extraction from Scanned Electronic Theses and Dissertations


ScanDL: A Diffusion Model for Generating Synthetic Scanpaths on Texts


ScanERU: Interactive 3D Visual Grounding based on Embodied Reference Understanding


ScanMix: Learning from Severe Label Noise via Semantic Clustering and Semi-Supervised Learning


ScanQA: 3D Question Answering for Spatial Scene Understanding


Scanflow: A multi-graph framework for Machine Learning workflow management, supervision, and debugging


Scanner: Efficient Video Analysis at Scale


Scanning For Dark Matter Subhalos in Hubble Space Telescope Imaging of 54 Strong Lenses


Scanning Only Once: An End-to-end Framework for Fast Temporal Grounding in Long Videos


Scanning Trojaned Models Using Out-of-Distribution Samples


Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized


ScarceNet: Animal Pose Estimation with Scarce Annotations


Scardina: Scalable Join Cardinality Estimation by Multiple Density Estimators


ScatSimCLR: self-supervised contrastive learning with pretext task regularization for small-scale datasets


ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention


ScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform Discharges


ScatterShot: Interactive In-context Example Curation for Text Transformation


ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning Problems


Scatterbrained: A flexible and expandable pattern for decentralized machine learning


Scattered Light Imaging: Resolving the substructure of nerve fiber crossings in whole brain sections with micrometer resolution


Scattered slice SHARD reconstruction for motion correction in multi-shell diffusion MRI


Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks


Scattering Model Guided Adversarial Examples for SAR Target Recognition: Attack and Defense


Scattering Parameter Measurements of the Long Wavelength Array Antenna and Front End Electronics


Scattering Quantum Random Walks on Square Grids and Randomly Generated Mazes


Scattering Transform Based Image Clustering using Projection onto Orthogonal Complement


Scattering amplitudes over finite fields and multivariate functional reconstruction


Scattering and inverse scattering for the AKNS system: A rational function approach


Scattering graph method for 3D radiative transfer


Scattering of Giant Planets and Implications for the Origin of the Hierarchical and Eccentric Two-planet System GJ 1148


Scattering of two and three physical pions at maximal isospin from lattice QCD


Scattering resonances in unbounded transmission problems with sign-changing coefficient


Scattering versus Forbidden Decay in Dark Matter Freeze-in


ScePT: Scene-consistent, Policy-based Trajectory Predictions for Planning


Scenario Execution for Robotics: A generic, backend-agnostic library for running reproducible robotics experiments and tests


Scenario-Based Curriculum Generation for Multi-Agent Autonomous Driving


Scenario-Based Field Testing of Drone Missions


Scenario-Based Test Reduction and Prioritization for Multi-Module Autonomous Driving Systems


Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark


ScenarioNet: Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling


Scene Adaptive Sparse Transformer for Event-based Object Detection


Scene Completeness-Aware Lidar Depth Completion for Driving Scenario


Scene Consistency Representation Learning for Video Scene Segmentation


Scene Designer: a Unified Model for Scene Search and Synthesis from Sketch


Scene Editing as Teleoperation: A Case Study in 6DoF Kit Assembly


Scene Graph Conditioning in Latent Diffusion


Scene Graph Generation from Objects, Phrases and Region Captions


Scene Graph Generation with Role-Playing Large Language Models


Scene Graph Modification Based on Natural Language Commands


Scene Graph as Pivoting: Inference-time Image-free Unsupervised Multimodal Machine Translation with Visual Scene Hallucination


Scene Informer: Anchor-based Occlusion Inference and Trajectory Prediction in Partially Observable Environments


Scene Parsing with Global Context Embedding


Scene Recognition by Combining Local and Global Image Descriptors


Scene Separation & Data Selection: Temporal Segmentation Algorithm for Real-Time Video Stream Analysis


Scene Synthesis via Uncertainty-Driven Attribute Synchronization


Scene Text Image Super-resolution based on Text-conditional Diffusion Models


Scene Text Recognition Models Explainability Using Local Features


Scene Text Recognition with Permuted Autoregressive Sequence Models


Scene Text Retrieval via Joint Text Detection and Similarity Learning


Scene learning, recognition and similarity detection in a fuzzy ontology via human examples


Scene relighting with illumination estimation in the latent space on an encoder-decoder scheme


Scene-Aware 3D Multi-Human Motion Capture from a Single Camera


Scene-Centric Unsupervised Panoptic Segmentation


Scene-Driven Exploration and GUI Modeling for Android Apps


Scene-Specific Pedestrian Detection Based on Parallel Vision


Scene-Text Grounding for Text-Based Video Question Answering


Scene-aware Egocentric 3D Human Pose Estimation


Scene-aware Human Motion Forecasting via Mutual Distance Prediction


Scene-centric vs. Object-centric Image-Text Cross-modal Retrieval: A Reproducibility Study


Scene-level Tracking and Reconstruction without Object Priors


Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover Classification


Scene-wise Adaptive Network for Dynamic Cold-start Scenes Optimization in CTR Prediction


SceneCraft: Layout-Guided 3D Scene Generation


SceneDreamer360: Text-Driven 3D-Consistent Scene Generation with Panoramic Gaussian Splatting


SceneDreamer: Unbounded 3D Scene Generation from 2D Image Collections


SceneFake: An Initial Dataset and Benchmarks for Scene Fake Audio Detection


SceneFormer: Indoor Scene Generation with Transformers


SceneGenAgent: Precise Industrial Scene Generation with Coding Agent


SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences


SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentation


SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields


SceneSplat: Gaussian Splatting-based Scene Understanding with Vision-Language Pretraining


SceneTracker: Long-term Scene Flow Estimation Network


Scenimefy: Learning to Craft Anime Scene via Semi-Supervised Image-to-Image Translation


Scent of Knowledge: Optimizing Search-Enhanced Reasoning with Information Foraging


SchNetPack 2.0: A neural network toolbox for atomistic machine learning


Schedulability Analysis in Time-Sensitive Networking: A Systematic Literature Review


Schedule optimization for transiting exoplanet observations with NASA's Pandora SmallSat mission


Scheduled Multi-task Learning for Neural Chat Translation


Scheduled Policy Optimization for Natural Language Communication with Intelligent Agents


Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent


Scheduled Sampling in Vision-Language Pretraining with Decoupled Encoder-Decoder Network


Scheduling Jobs with Stochastic Holding Costs


Scheduling Servers with Stochastic Bilinear Rewards


Scheduling Virtual Conferences Fairly: Achieving Equitable Participant and Speaker Satisfaction


Scheduling of Missions with Constrained Tasks for Heterogeneous Robot Systems


Scheduling periodic messages on a shared link


Scheherazade: Evaluating Chain-of-Thought Math Reasoning in LLMs with Chain-of-Problems


Schema Inference for Interpretable Image Classification


Schema Matching with Large Language Models: an Experimental Study


Schema-Driven Information Extraction from Heterogeneous Tables


Schema-Guided Natural Language Generation


Schema-Guided Paradigm for Zero-Shot Dialog


Schema-Guided Semantic Accuracy: Faithfulness in Task-Oriented Dialogue Response Generation


Schema-Guided User Satisfaction Modeling for Task-Oriented Dialogues


Schema-R1: A reasoning training approach for schema linking in Text-to-SQL Task


Schema-adaptable Knowledge Graph Construction


Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction


SchemaAgent: A Multi-Agents Framework for Generating Relational Database Schema


Schlieren and BOS velocimetry of a round turbulent helium jet in air


SchoenbAt: Rethinking Attention with Polynomial basis


Schoenberg-Rao distances: Entropy-based and geometry-aware statistical Hilbert distances


Scholarly Knowledge Graph Construction from Published Software Packages


Scholarly Question Answering using Large Language Models in the NFDI4DataScience Gateway


Scholarly Wikidata: Population and Exploration of Conference Data in Wikidata using LLMs


Scholia and scientometrics with Wikidata


School Virus Infection Simulator for Customizing School Schedules During COVID-19


Schooling and Labor Market Consequences of School Construction in Indonesia: Comment


Schools as a Safety-net: The Impact of School Closures and Reopenings on Rates of Reporting of Violence Against Children


Schroedinger's Threshold: When the AUC doesn't predict Accuracy


Schroedinger's code: A preliminary study on research source code availability and link persistence in astrophysics


Schrödinger's Bat: Diffusion Models Sometimes Generate Polysemous Words in Superposition


Schrödinger's Camera: First Steps Towards a Quantum-Based Privacy Preserving Camera


SchurVINS: Schur Complement-Based Lightweight Visual Inertial Navigation System


Schwarzschild and Ledoux are equivalent on evolutionary timescales


Schwarzschild metric from Scattering Amplitudes to all orders in $G_N$


Sci-LoRA: Mixture of Scientific LoRAs for Cross-Domain Lay Paraphrasing


SciAnnotate: A Tool for Integrating Weak Labeling Sources for Sequence Labeling


SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis


SciBERT-based Semantification of Bioassays in the Open Research Knowledge Graph


SciBERT: A Pretrained Language Model for Scientific Text


SciBERTSUM: Extractive Summarization for Scientific Documents


SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models


SciCap+: A Knowledge Augmented Dataset to Study the Challenges of Scientific Figure Captioning


SciCap: Generating Captions for Scientific Figures


SciConNav: Knowledge navigation through contextual learning of extensive scientific research trajectories


SciDQA: A Deep Reading Comprehension Dataset over Scientific Papers


SciDTB: Discourse Dependency TreeBank for Scientific Abstracts


SciDaSynth: Interactive Structured Knowledge Extraction and Synthesis from Scientific Literature with Large Language Model


SciDataFlow: A Tool for Improving the Flow of Data through Science


SciER: An Entity and Relation Extraction Dataset for Datasets, Methods, and Tasks in Scientific Documents


SciEvo: A 2 Million, 30-Year Cross-disciplinary Dataset for Temporal Scientometric Analysis


SciEx: Benchmarking Large Language Models on Scientific Exams with Human Expert Grading and Automatic Grading


SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation


SciFact-Open: Towards open-domain scientific claim verification


SciFaultyQA: Benchmarking LLMs on Faulty Science Question Detection with a GAN-Inspired Approach to Synthetic Dataset Generation


SciFive: a text-to-text transformer model for biomedical literature


SciFix: Outperforming GPT3 on Scientific Factual Error Correction


SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs


SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models


SciKGTeX -- A LaTeX Package to Semantically Annotate Contributions in Scientific Publications


SciKnowEval: Evaluating Multi-level Scientific Knowledge of Large Language Models


SciLander: Mapping the Scientific News Landscape


SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation


SciMMIR: Benchmarking Scientific Multi-modal Information Retrieval


SciMON: Scientific Inspiration Machines Optimized for Novelty


SciNLI: A Corpus for Natural Language Inference on Scientific Text


SciPIP: An LLM-based Scientific Paper Idea Proposer


SciPrompt: Knowledge-augmented Prompting for Fine-grained Categorization of Scientific Topics


SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python


SciQu: Accelerating Materials Properties Prediction with Automated Literature Mining for Self-Driving Laboratories


SciREX: A Challenge Dataset for Document-Level Information Extraction


SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature


SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research Papers


SciSports: Learning football kinematics through two-dimensional tracking data


SciTweets -- A Dataset and Annotation Framework for Detecting Scientific Online Discourse


Science Hierarchography: Hierarchical Organization of Science Literature


Science In the Cloud (SIC): A use case in MRI Connectomics


Science Out of Its Ivory Tower: Improving Accessibility with Reinforcement Learning


Science is Exploration: Computational Frontiers for Conceptual Metaphor Theory


Science-Driven Optimization of the LSST Observing Strategy


ScienceMeter: Tracking Scientific Knowledge Updates in Language Models


ScienceWorld: Is your Agent Smarter than a 5th Grader?


Scientific Article Summarization Using Citation-Context and Article's Discourse Structure


Scientific Calculator for Designing Trojan Detectors in Neural Networks


Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers


Scientific Discourse Tagging for Evidence Extraction


Scientific Discovery by Generating Counterfactuals using Image Translation


Scientific Language Models for Biomedical Knowledge Base Completion: An Empirical Study


Scientific Large Language Models: A Survey on Biological & Chemical Domains


Scientific Opinion Summarization: Paper Meta-review Generation Dataset, Methods, and Evaluation


Scientific and Creative Analogies in Pretrained Language Models


Scientific and technological knowledge grows linearly over time


Scientific productivity as a random walk


Scientometric Review of Artificial Intelligence for Operations & Maintenance of Wind Turbines: The Past, Present and Future


Scikit-Multiflow: A Multi-output Streaming Framework


Scikit-dimension: a Python package for intrinsic dimension estimation


Scikit-network: Graph Analysis in Python


Scilla: a Smart Contract Intermediate-Level LAnguage


Scim: Intelligent Skimming Support for Scientific Papers


ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing


Scission: Performance-driven and Context-aware Cloud-Edge Distribution of Deep Neural Networks


Scissorhands: Scrub Data Influence via Connection Sensitivity in Networks


ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning


Scope Ambiguities in Large Language Models


Scope Restriction for Scalable Real-Time Railway Rescheduling: An Exploratory Study


Scope-enhanced Compositional Semantic Parsing for DRT


Scope2Screen: Focus+Context Techniques for Pathology Tumor Assessment in Multivariate Image Data


ScopeFlow: Dynamic Scene Scoping for Optical Flow


Scoping Review of Active Learning Strategies and their Evaluation Environments for Entity Recognition Tasks


Score Matched Neural Exponential Families for Likelihood-Free Inference


Score Mismatching for Generative Modeling


Score Normalization for a Faster Diffusion Exponential Integrator Sampler


Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising


Score Regularized Policy Optimization through Diffusion Behavior


Score Transformer: Generating Musical Score from Note-level Representation


Score matching for bridges without learning time-reversals


Score refinement for confidence-based 3D multi-object tracking


Score-Based Change Detection for Gradient-Based Learning Machines


Score-Based Diffusion Policy Compatible with Reinforcement Learning via Optimal Transport


Score-Based Generative Modeling with Critically-Damped Langevin Diffusion


Score-Based Generative Models for Designing Binding Peptide Backbones


Score-Based Generative Models for PET Image Reconstruction


Score-Guided Diffusion for 3D Human Recovery


Score-balanced Loss for Multi-aspect Pronunciation Assessment


Score-based 3D molecule generation with neural fields


Score-based Diffusion Models for Generating Liquid Argon Time Projection Chamber Images


Score-based Generative Diffusion Models for Social Recommendations


Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance


Score-based Generative Modeling for Conditional Independence Testing


Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations


Score-based Generative Models for Calorimeter Shower Simulation


Score-based Source Separation with Applications to Digital Communication Signals


Score-based calibration testing for multivariate forecast distributions


Score-based change point detection via tracking the best of infinitely many experts


Score-based diffusion models for accelerated MRI


Score-based diffusion priors for multi-target detection


Score-informed Music Source Separation: Improving Synthetic-to-real Generalization in Classical Music


Score-informed Networks for Music Performance Assessment


Score-informed syllable segmentation for a cappella singing voice with convolutional neural networks


ScoreAdv: Score-based Targeted Generation of Natural Adversarial Examples via Diffusion Models


ScoreDrivenModels.jl: a Julia Package for Generalized Autoregressive Score Models


ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference Optimization


ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models


ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification


Scoring Coreference Chains with Split-Antecedent Anaphors


Scoring Cycling Environments Perceived Safety using Pairwise Image Comparisons


Scoring Rules and Calibration for Imprecise Probabilities


Scoring Time Intervals using Non-Hierarchical Transformer For Automatic Piano Transcription


Scoring with Large Language Models: A Study on Measuring Empathy of Responses in Dialogues


Scoring-Assisted Generative Exploration for Proteins (SAGE-Prot): A Framework for Multi-Objective Protein Optimization via Iterative Sequence Generation and Evaluation


Scorpiano -- A System for Automatic Music Transcription for Monophonic Piano Music


Scraping SERPs for Archival Seeds: It Matters When You Start


Scraping Social Media Photos Posted in Kenya and Elsewhere to Detect and Analyze Food Types


Scrappy: SeCure Rate Assuring Protocol with PrivacY


ScratchDet: Training Single-Shot Object Detectors from Scratch


ScratchEval: Are GPT-4o Smarter than My Child? Evaluating Large Multimodal Models with Visual Programming Challenges


Scratchy: A Lightweight Modular Autonomous Robot for Robotic Competitions


ScreeNOT: Exact MSE-Optimal Singular Value Thresholding in Correlated Noise


Screen & Relax: Accelerating the resolution of Elastic-net by safe identification of the solution support


Screen2Vec: Semantic Embedding of GUI Screens and GUI Components


Screen2Words: Automatic Mobile UI Summarization with Multimodal Learning


ScreenAI: A Vision-Language Model for UI and Infographics Understanding


ScreenAgent: A Vision Language Model-driven Computer Control Agent


ScreenExplorer: Training a Vision-Language Model for Diverse Exploration in Open GUI World


Screening Mammography Breast Cancer Detection


Screening Sinkhorn Algorithm for Regularized Optimal Transport


Screening of BindingDB database ligands against EGFR, HER2, Estrogen, Progesterone and NF-kB receptors based on machine learning and molecular docking


ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory


ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation


Scribble Hides Class: Promoting Scribble-Based Weakly-Supervised Semantic Segmentation with Its Class Label


Scribble-Guided Diffusion for Training-free Text-to-Image Generation


Scribble-Supervised LiDAR Semantic Segmentation


Scribble-Supervised RGB-T Salient Object Detection


Scribble-Supervised Target Extraction Method Based on Inner Structure-Constraint for Remote Sensing Images


Scribble-based Boundary-aware Network for Weakly Supervised Salient Object Detection in Remote Sensing Images


Scribble-based Domain Adaptation via Co-segmentation


Scribble-based Weakly Supervised Deep Learning for Road Surface Extraction from Remote Sensing Images


Scribble-based fast weak-supervision and interactive corrections for segmenting whole slide images


Scribble-supervised Cell Segmentation Using Multiscale Contrastive Regularization


Scribble2D5: Weakly-Supervised Volumetric Image Segmentation via Scribble Annotations


Scribble2Label: Scribble-Supervised Cell Segmentation via Self-Generating Pseudo-Labels with Consistency


ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical Image


ScribbleVC: Scribble-supervised Medical Image Segmentation with Vision-Class Embedding


ScribbleVS: Scribble-Supervised Medical Image Segmentation via Dynamic Competitive Pseudo Label Selection


Scribbles for All: Benchmarking Scribble Supervised Segmentation Across Datasets


ScribeAgent: Towards Specialized Web Agents Using Production-Scale Workflow Data


Script Identification in Natural Scene Image and Video Frame using Attention based Convolutional-LSTM Network


Script Normalization for Unconventional Writing of Under-Resourced Languages in Bilingual Communities


ScriptWorld: Text Based Environment For Learning Procedural Knowledge


ScriptWriter: Narrative-Guided Script Generation


ScrofaZero: Mastering Trick-taking Poker Game Gongzhu by Deep Reinforcement Learning


ScrollNet: Dynamic Weight Importance for Continual Learning


Scrolling in the Deep: Analysing Contextual Influences on Intervention Effectiveness during Infinite Scrolling on Social Media


Scrooge Attack: Undervolting ARM Processors for Profit


Scruples: A Corpus of Community Ethical Judgments on 32,000 Real-Life Anecdotes


Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning


Scrutinizer: A Mixed-Initiative Approach to Large-Scale, Data-Driven Claim Verification


Scrutinizing XAI using linear ground-truth data with suppressor variables


Sculpting Features from Noise: Reward-Guided Hierarchical Diffusion for Task-Optimal Feature Transformation


Sculpting Holistic 3D Representation in Contrastive Language-Image-3D Pre-training


Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning


SdAE: Self-distillated Masked Autoencoder


SdCT-GAN: Reconstructing CT from Biplanar X-Rays with Self-driven Generative Adversarial Networks


SeA: Semantic Adversarial Augmentation for Last Layer Features from Unsupervised Representation Learning


SeACo-Paraformer: A Non-Autoregressive ASR System with Flexible and Effective Hotword Customization Ability


SeBot: Structural Entropy Guided Multi-View Contrastive Learning for Social Bot Detection


SeCG: Semantic-Enhanced 3D Visual Grounding via Cross-modal Graph Attention


SeCap: Self-Calibrating and Adaptive Prompts for Cross-view Person Re-Identification in Aerial-Ground Networks


SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning


SeD: Semantic-Aware Discriminator for Image Super-Resolution


SeDR: Segment Representation Learning for Long Documents Dense Retrieval


SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings


SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization


SeFNet: Bridging Tabular Datasets with Semantic Feature Nets


SeGA: Preference-Aware Self-Contrastive Learning with Prompts for Anomalous User Detection on Twitter


SeGAN: Segmenting and Generating the Invisible


SeGraM: A Universal Hardware Accelerator for Genomic Sequence-to-Graph and Sequence-to-Sequence Mapping


SeLR: Sparsity-enhanced Lagrangian Relaxation for Computation Offloading at the Edge


SeLeP: Learning Based Semantic Prefetching for Exploratory Database Workloads


SeLoC-ML: Semantic Low-Code Engineering for Machine Learning Applications in Industrial IoT


SeMLaPS: Real-time Semantic Mapping with Latent Prior Networks and Quasi-Planar Segmentation


SeMantic AnsweR Type prediction task (SMART) at ISWC 2020 Semantic Web Challenge


SeMask: Semantically Masked Transformers for Semantic Segmentation


SeMemNN: A Semantic Matrix-Based Memory Neural Network for Text Classification


SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder


SePPO: Semi-Policy Preference Optimization for Diffusion Alignment


SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction


SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation


SeRL: Self-Play Reinforcement Learning for Large Language Models with Limited Data


SeRO: Self-Supervised Reinforcement Learning for Recovery from Out-of-Distribution Situations


SeReMAS: Self-Resilient Mobile Autonomous Systems Through Predictive Edge Computing


SeSaMe: A Framework to Simulate Self-Reported Ground Truth for Mental Health Sensing Studies


SeSame: Simple, Easy 3D Object Detection with Point-Wise Semantics


SeSeMI: Secure Serverless Model Inference on Sensitive Data


SeTAR: Out-of-Distribution Detection with Selective Low-Rank Approximation


SeVeN: Augmenting Word Embeddings with Unsupervised Relation Vectors


SeaDroneSim: Simulation of Aerial Images for Detection of Objects Above Water


SeaFormer++: Squeeze-enhanced Axial Transformer for Mobile Visual Recognition


SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation


SeaS: Few-shot Industrial Anomaly Image Generation with Separation and Sharing Fine-tuning


SeaThru-NeRF: Neural Radiance Fields in Scattering Media


SeafloorAI: A Large-scale Vision-Language Dataset for Seafloor Geological Survey


Seal-3D: Interactive Pixel-Level Editing for Neural Radiance Fields


Seal-Tools: Self-Instruct Tool Learning Dataset for Agent Tuning and Detailed Benchmark


Seamless Detection: Unifying Salient Object Detection and Camouflaged Object Detection


Seamless Human Motion Composition with Blended Positional Encodings


Seamless Integration of Tactile Sensors for Cobots


Seamless Monitoring of Stress Levels Leveraging a Universal Model for Time Sequences


Seamless Variability Management With the Virtual Platform


Seamless and multi-resolution energy forecasting


Seamless lightning nowcasting with recurrent-convolutional deep learning


Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-Start Users


SeanNet: Semantic Understanding Network for Localization Under Object Dynamics


Search Algorithms for Automated Hyper-Parameter Tuning


Search Arena: Analyzing Search-Augmented LLMs


Search Behavior Prediction: A Hypergraph Perspective


Search Disaster Victims using Sound Source Localization


Search Efficient Binary Network Embedding


Search Trajectories Networks of Multiobjective Evolutionary Algorithms


Search Wide, Focus Deep: Automated Fetal Brain Extraction with Sparse Training Data


Search and Explore: Symbiotic Policy Synthesis in POMDPs


Search and Learn: Improving Semantic Coverage for Data-to-Text Generation


Search and Refine During Think: Autonomous Retrieval-Augmented Reasoning of LLMs


Search and Score-based Waterfall Auction Optimization


Search for Coincident Gravitational Wave and Long Gamma-Ray Bursts from 4-OGC and the Fermi-GBM/Swift-BAT Catalog


Search for Coincident Gravitational-wave and Fast Radio Burst Events from 4-OGC and the First CHIME/FRB Catalog


Search for Cosmological time dilation from Gamma-Ray Bursts -- A 2021 status update


Search for Efficient Large Language Models


Search for Galaxy Cluster Candidates in the Cosmic Microwave Background Maps of the Planck Space Mission Using a Convolutional Neural Network Based on the Method of Tracing the Sunyaev-Zeldovich Effect


Search for Hidden Neutrinos at the European Spallation Source: the SHiNESS experiment


Search for Invariant Sets of the Generalized Tent Map


Search for associations containing young stars (SACY) VIII. An updated census of spectroscopic binary systems showing hints of non-universal multiplicity among these associations


Search for black hole hyperbolic encounters with gravitational wave detectors


Search for dark photons in heavy-ion collisions


Search for dark photons using a multilayer dielectric haloscope equipped with a single-photon avalanche diode


Search for eccentric NSBH and BNS mergers in the third observing run of Advanced LIGO and Virgo


Search for extended sources in the images from Chandra X-ray Observatory Advanced CCD Imaging Spectrometer


Search for gravitational waves from high-mass-ratio compact-binary mergers of stellar mass and sub-solar mass black holes


Search for gravitational waves from the coalescence of sub-solar mass and eccentric compact binaries


Search for gravitational waves from the coalescence of sub-solar mass binaries in the first half of Advanced LIGO and Virgo's third observing run


Search for low mass dark matter in DarkSide-50: the bayesian network approach


Search for strongly lensed counterpart images of binary black hole mergers in the first two LIGO observing runs


Search for temporal cell segmentation robustness in phase-contrast microscopy videos


Search is All You Need for Few-shot Anomaly Detection


Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification


Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks


Search to Pass Messages for Temporal Knowledge Graph Completion


Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering


Search-Based Regular Expression Inference on a GPU


Search-Based Software Engineering for Self-Adaptive Systems: Survey, Disappointments, Suggestions and Opportunities


Search-Engine-augmented Dialogue Response Generation with Cheaply Supervised Query Production


Search-based Crash Reproduction using Behavioral Model Seeding


Search-based Software Testing Driven by Automatically Generated and Manually Defined Fitness Functions


Search-based versus Sampling-based Robot Motion Planning: A Comparative Study


Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks


Search4Code: Code Search Intent Classification Using Weak Supervision


SearchFromFree: Adversarial Measurements for Machine Learning-based Energy Theft Detection


Searching High Temperature Superconductors with the assistance of Graph Neural Networks


Searching Mobile App Screens via Text + Doodle


Searching Multi-Rate and Multi-Modal Temporal Enhanced Networks for Gesture Recognition


Searching Parameterized AP Loss for Object Detection


Searching for Ambiguous Objects in Videos using Relational Referring Expressions


Searching for Axial Neutral Current Non-Standard Interactions of neutrinos by DUNE-like experiments


Searching for Best Practices in Medical Transcription with Large Language Model


Searching for Best Practices in Retrieval-Augmented Generation


Searching for Effective Neural Network Architectures for Heart Murmur Detection from Phonocardiogram


Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices


Searching for Efficient Multi-Stage Vision Transformers


Searching for Historical Extragalactic Optical Transients Associated with Fast Radio Bursts


Searching for Low-mass Population III Stars Disguised as White Dwarfs


Searching for Multi-Fault Programs in Defects4J


Searching for Network Width with Bilaterally Coupled Network


Searching for Optimal Subword Tokenization in Cross-domain NER


Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms


Searching for Programmatic Policies in Semantic Spaces


Searching for Rigidity in Algebraic Starscapes


Searching for Smurfs: Testing if Money Launderers Know Alert Thresholds


Searching for Structure in Unfalsifiable Claims


Searching for Ultralight Dark Matter Conversion in Solar Corona using Low Frequency Array Data


Searching for X-Ray Counterparts of Degree Wide TeV Halos Around Middle-Aged Pulsars with SRG/eROSITA


Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples


Searching for a source without gradients: how good is infotaxis and how to beat it


Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution


Searching for consistent associations with a multi-environment knockoff filter


Searching for dark energy in the matter-dominated era


Searching for dark matter subhalos in the Fermi-LAT catalog with Bayesian neural networks


Searching for dark-matter waves with PPTA and QUIJOTE pulsar polarimetry


Searching for electromagnetic counterpart of LIGO gravitational waves in the Fermi GBM data with ADWO


Searching for low-redshift faint galaxies with MMT/Hectospec


Searching for outliers in the Chandra Source Catalog


Searching for pulsars with phase characteristics


Searching for quasi-periodic oscillations in astrophysical transients using Gaussian processes


Searching for solar-like oscillations in pre-main sequence stars using APOLLO


Searching for waveforms on spatially-filtered epileptic ECoG


Searching from Area to Point: A Hierarchical Framework for Semantic-Geometric Combined Feature Matching


Searching on the boundary of abundance for odd weird numbers


Searching the Entirety of Kepler Data. II. Occurrence Rate Estimates for FGK Stars


Searching to Learn with Instructional Scaffolding


Searching towards Class-Aware Generators for Conditional Generative Adversarial Networks


SeasFire as a Multivariate Earth System Datacube for Wildfire Dynamics


Season-invariant GNSS-denied visual localization for UAVs


SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark under Multiple Environments


Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification


Seasonal Performance Evaluation of a Hybrid PV-Wind-Battery Power System for a Mars Base


Seasonality and spatial dependence of meso- and submesoscale ocean currents from along-track satellite altimetry


Seasonality and susceptibility from measles time series


Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal Data


Sebica: Lightweight Spatial and Efficient Bidirectional Channel Attention Super Resolution Network


Sebis at SemEval-2023 Task 7: A Joint System for Natural Language Inference and Evidence Retrieval from Clinical Trial Reports


Sebra: Debiasing Through Self-Guided Bias Ranking


Sec2Sec Co-attention for Video-Based Apparent Affective Prediction


Sec5GLoc: Securing 5G Indoor Localization via Adversary-Resilient Deep Learning Architecture


SecAlign: Defending Against Prompt Injection with Preference Optimization


SecCAN: An Extended CAN Controller with Embedded Intrusion Detection


SecDocker: Hardening the Continuous Integration Workflow


SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding


SecFormer: Fast and Accurate Privacy-Preserving Inference for Transformer Models via SMPC


SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security


SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection


Secant Penalized BFGS: A Noise Robust Quasi-Newton Method Via Penalizing The Secant Condition


Secant varieties of Segre-Veronese varieties $\mathbb{P}^m\times\mathbb{P}^n$ embedded by $\mathcal{O}(1,2)$ are non-defective for $n\gg m^3$, $m\geq3$


Second Language Acquisition of Neural Language Models


Second Maximum of a Gaussian Random Field and Exact (t-)Spacing test


Second Order Threshold Dynamics Schemes for Two Phase Motion by Mean Curvature


Second language Korean Universal Dependency treebank v1.2: Focus on data augmentation and annotation scheme refinement


Second order symmetry operators for the massive Dirac equation


Second- and third-order properties of multidimensional Langevin equations


Second-Order Adjoint Method for Quantum Optimal Control


Second-Order Conic and Polyhedral Approximations of the Exponential Cone: Application to Mixed-Integer Exponential Conic Programs


Second-Order Pooling for Graph Neural Networks


Second-Order Stochastic Optimization for Machine Learning in Linear Time


Second-Order Switching Time Optimization for Switched Dynamical Systems


Second-Order Unsupervised Neural Dependency Parsing


Second-order Co-occurrence Sensitivity of Skip-Gram with Negative Sampling


Second-order Conditional Gradient Sliding


Second-order Teukolsky formalism in Kerr spacetime: formulation and nonlinear source


Second-order differential operators, stochastic differential equations and Brownian motions on embedded manifolds


Second-order optimisation strategies for neural network quantum states


Second-order robust parallel integrators for dynamical low-rank approximation


Second-order variational equations for N-body simulations


SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimation


Secondary Protein Structure Prediction Using Neural Networks


Secondary Structure-Guided Novel Protein Sequence Generation with Latent Graph Diffusion


Secondary Vertex Finding in Jets with Neural Networks


Secondary control activation analysed and predicted with explainable AI


Secret Breach Prevention in Software Issue Reports


SecretBench: A Dataset of Software Secrets


SecretGen: Privacy Recovery on Pre-Trained Models via Distribution Discrimination


Secrets Revealed in Container Images: An Internet-wide Study on Occurrence and Impact


Sector Volatility Prediction Performance Using GARCH Models and Artificial Neural Networks


Sectored DRAM: A Practical Energy-Efficient and High-Performance Fine-Grained DRAM Architecture


SecuCode: Intrinsic PUF Entangled Secure Wireless Code Dissemination for Computational RFID Devices


Secure Aggregation is Not Private Against Membership Inference Attacks


Secure Cloud Storage with Client-Side Encryption Using a Trusted Execution Environment


Secure Cloud-Edge Deployments, with Trust


Secure Collaborative Training and Inference for XGBoost


Secure Communication Model For Quantum Federated Learning: A Post Quantum Cryptography (PQC) Framework


Secure Content-Based Routing Using Intel Software Guard Extensions


Secure Control Systems for Autonomous Quadrotors against Cyber-Attacks


Secure Domain Adaptation with Multiple Sources


Secure Evaluation of Knowledge Graph Merging Gain


Secure Federated Learning against Model Poisoning Attacks via Client Filtering


Secure Multi-Key Homomorphic Encryption with Application to Privacy-Preserving Federated Learning


Secure Multi-Party Computation for Inter-Organizational Process Mining


Secure On-Device Video OOD Detection Without Backpropagation


Secure Parsing and Serializing with Separation Logic Applied to CBOR, CDDL, and COSE


Secure SAML validation to prevent XML signature wrapping attacks


Secure Safety Filter Design for Sampled-data Nonlinear Systems under Sensor Spoofing Attacks


Secure Safety Filter: Towards Safe Flight Control under Sensor Attacks


Secure Service Implementation with Slice Isolation and WireGuard


Secure Shapley Value for Cross-Silo Federated Learning (Technical Report)


Secure Summation via Subset Sums: A New Primitive for Privacy-Preserving Distributed Machine Learning


Secure Targeted Message Dissemination in IoT Using Blockchain Enabled Edge Computing


Secure Time-Modulated Intelligent Reflecting Surface via Generative Flow Networks


Secure and Accurate Summation of Many Floating-Point Numbers


Secure and Authorized Client-to-Client Communication for LwM2M


Secure and Efficient General Matrix Multiplication On Cloud Using Homomorphic Encryption


Secure and trustworthy file sharing over cloud storage using eID tokens


Secure multi-party linear regression at plaintext speed


Secure numerical simulations using fully homomorphic encryption


SecureBERT: A Domain-Specific Language Model for Cybersecurity


SecureGaze: Defending Gaze Estimation Against Backdoor Attacks


SecureLLM: Using Compositionality to Build Provably Secure Language Models for Private, Sensitive, and Secret Data


SecurePtrs: Proving Secure Compilation with Data-Flow Back-Translation and Turn-Taking Simulation


SecureSpectra: Safeguarding Digital Identity from Deep Fake Threats via Intelligent Signatures


SecureStreams: A Reactive Middleware Framework for Secure Data Stream Processing


Secured Communication Schemes for UAVs in 5G: CRYSTALS-Kyber and IDS


Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples


Securely implementing and managing neighborhood solar with storage and peer to peer transactive energy


Securing AI Agents with Information-Flow Control


Securing Data in Multimode Fibers by Exploiting Mode-Dependent Light Propagation Effects


Securing Deep Generative Models with Universal Adversarial Signature


Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters


Securing Distributed SGD against Gradient Leakage Threats


Securing Federated Sensitive Topic Classification against Poisoning Attacks


Securing Healthcare with Deep Learning: A CNN-Based Model for medical IoT Threat Detection


Securing Multi-turn Conversational Language Models From Distributed Backdoor Triggers


Securing Neural Networks with Knapsack Optimization


Securing Recommender System via Cooperative Training


Securing name resolution in the IoT: DNS over CoAP


Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks


Security Analysis of Vendor Implementations of the OPC UA Protocol for Industrial Control Systems


Security Analysis of the Consumer Remote SIM Provisioning Protocol


Security Assessment of Hierarchical Federated Deep Learning


Security Attacks on LLM-based Code Completion Tools


Security Properties for Open-Source Hardware Designs


Security and Machine Learning Adoption in IoT: A Preliminary Study of IoT Developer Discussions


Security and Privacy Measurement on Chinese Consumer IoT Traffic based on Device Lifecycle


Security and Privacy of Lightning Network Payments with Uncertain Channel Balances


Security of Alerting Authorities in the WWW: Measuring Namespaces, DNSSEC, and Web PKI


Security of Language Models for Code: A Systematic Literature Review


Security, Privacy, and Decentralization in Web3


SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models


SedarEval: Automated Evaluation using Self-Adaptive Rubrics


Sedimentation of a surfactant-laden drop in a liquid with particles


See Detail Say Clear: Towards Brain CT Report Generation via Pathological Clue-driven Representation Learning


See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation


See It from My Perspective: Diagnosing the Western Cultural Bias of Large Vision-Language Models in Image Understanding


See More Details: Efficient Image Super-Resolution by Experts Mining


See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks


See Through Smoke: Robust Indoor Mapping with Low-cost mmWave Radar


See Through Their Minds: Learning Transferable Neural Representation from Cross-Subject fMRI


See What I Mean? Expressiveness and Clarity in Robot Display Design


See What LLMs Cannot Answer: A Self-Challenge Framework for Uncovering LLM Weaknesses


See or Guess: Counterfactually Regularized Image Captioning


See through the Dark: Learning Illumination-affined Representations for Nighttime Occupancy Prediction


See to Believe: Using Visualization To Motivate Updating Third-party Dependencies


See, Think, Confirm: Interactive Prompting Between Vision and Language Models for Knowledge-based Visual Reasoning


See360: Novel Panoramic View Interpolation


SeeABLE: Soft Discrepancies and Bounded Contrastive Learning for Exposing Deepfakes


SeeAction: Towards Reverse Engineering How-What-Where of HCI Actions from Screencasts for UI Automation


SeeChart: Enabling Accessible Visualizations Through Interactive Natural Language Interface For People with Visual Impairments


SeeClear: Semantic Distillation Enhances Pixel Condensation for Video Super-Resolution


SeeDS: Semantic Separable Diffusion Synthesizer for Zero-shot Food Detection


SeeGULL Multilingual: a Dataset of Geo-Culturally Situated Stereotypes


SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models


SeeHow: Workflow Extraction from Programming Screencasts through Action-Aware Video Analytics


SeePrivacy: Automated Contextual Privacy Policy Generation for Mobile Applications


SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution


SeeSaw: Interactive Ad-hoc Search Over Image Databases


SeeWasm: An Efficient and Fully-Functional Symbolic Execution Engine for WebAssembly Binaries


Seed Word Selection for Weakly-Supervised Text Classification with Unsupervised Error Estimation


Seed banks can help to maintain the diversity of interacting phytoplankton species


Seed-Coder: Let the Code Model Curate Data for Itself


Seed-Free Synthetic Data Generation Framework for Instruction-Tuning LLMs: A Case Study in Thai


Seed-Guided Fine-Grained Entity Typing in Science and Engineering Domains


Seed-Guided Topic Discovery with Out-of-Vocabulary Seeds


Seed-Point Based Geometric Partitioning of Nuclei Clumps


Seed-Point Detection of Clumped Convex Objects by Short-Range Attractive Long-Range Repulsive Particle Clustering


Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study


SeedBench: A Multi-task Benchmark for Evaluating Large Language Models in Seed Science


SeedFormer: Patch Seeds based Point Cloud Completion with Upsample Transformer


SeedGNN: Graph Neural Networks for Supervised Seeded Graph Matching


SeedTree: A Dynamically Optimal and Local Self-Adjusting Tree


Seeded Poisson Factorization: Leveraging domain knowledge to fit topic models


Seeded iterative clustering for histology region identification


Seeding Contradiction: a fast method for generating full-coverage test suites


Seeding neural network quantum states with tensor network states


Seeding with Differentially Private Network Information


Seeing All the Angles: Learning Multiview Manipulation Policies for Contact-Rich Tasks from Demonstrations


Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar


Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding


Seeing Double: Calibrating Two Jets at Once


Seeing Eye to AI: Human Alignment via Gaze-Based Response Rewards for Large Language Models


Seeing Far in the Dark with Patterned Flash


Seeing Is Not Always Believing: Invisible Collision Attack and Defence on Pre-Trained Models


Seeing Motion at Nighttime with an Event Camera


Seeing Red: PPG Biometrics Using Smartphone Cameras


Seeing Sarcasm Through Different Eyes: Analyzing Multimodal Sarcasm Perception in Large Vision-Language Models


Seeing The Whole Patient: Using Multi-Label Medical Text Classification Techniques to Enhance Predictions of Medical Codes


Seeing Through AI's Lens: Enhancing Human Skepticism Towards LLM-Generated Fake News


Seeing Through the Glass: Neural 3D Reconstruction of Object Inside a Transparent Container


Seeing Through the Mask: Rethinking Adversarial Examples for CAPTCHAs


Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert


Seeing and Hearing Egocentric Actions: How Much Can We Learn?


Seeing and hearing what has not been said; A multimodal client behavior classifier in Motivational Interviewing with interpretable fusion


Seeing from Another Perspective: Evaluating Multi-View Understanding in MLLMs


Seeing into Darkness: Scotopic Visual Recognition


Seeing is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability


Seeing is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided Decoding


Seeing is Not Reasoning: MVPBench for Graph-based Evaluation of Multi-path Visual Physical CoT


Seeing is Understanding: Unlocking Causal Attention into Modality-Mutual Attention for Multimodal LLMs


Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection


Seeing the Abstract: Translating the Abstract Language for Vision Language Models


Seeing the Forest for the Trees: A Large Scale, Continuously Updating Meta-Analysis of Frontier LLMs


Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients


Seeing the Future, Perceiving the Future: A Unified Driving World Model for Future Generation and Perception


Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment


Seeing the Pose in the Pixels: Learning Pose-Aware Representations in Vision Transformers


Seeing the Unseen: Learning Basis Confounder Representations for Robust Traffic Prediction


Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers


Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery


Seeing through the CO2 plume: joint inversion-segmentation of the Sleipner 4D Seismic Dataset


Seeing your sleep stage: cross-modal distillation from EEG to infrared video


Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space


Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model


Seeking Commonness and Inconsistencies: A Jointly Smoothed Approach to Multi-view Subspace Clustering


Seeking Diverse Reasoning Logic: Controlled Equation Expression Generation for Solving Math Word Problems


Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective


Seeking Patterns, Not just Memorizing Procedures: Contrastive Learning for Solving Math Word Problems


Seeking Quality Diversity in Evolutionary Co-design of Morphology and Control of Soft Tensegrity Modular Robots


Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection


Seeking the Building Blocks of Visual Imagery and Creativity in a Cognitively Inspired Neural Network


Seeking the Shape of Sound: An Adaptive Framework for Learning Voice-Face Association


Seemingly Plausible Distractors in Multi-Hop Reasoning: Are Large Language Models Attentive Readers?


Seen to Unseen: Exploring Compositional Generalization of Multi-Attribute Controllable Dialogue Generation


Seernet at EmoInt-2017: Tweet Emotion Intensity Estimator


Seg-LSTM: Performance of xLSTM for Semantic Segmentation of Remotely Sensed Images


Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning


Seg-Wild: Interactive Segmentation based on 3D Gaussian Splatting for Unconstrained Image Collections


Seg-metrics: a Python package to compute segmentation metrics


Seg2Act: Global Context-aware Action Generation for Document Logical Structuring


SegACIL: Solving the Stability-Plasticity Dilemma in Class-Incremental Semantic Segmentation


SegAnyPET: Universal Promptable Segmentation from Positron Emission Tomography Images


SegAugment: Maximizing the Utility of Speech Translation Data with Segmentation-based Augmentations


SegBlocks: Block-Based Dynamic Resolution Networks for Real-Time Segmentation


SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation


SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy data


SegDiff: Image Segmentation with Diffusion Probabilistic Models


SegEarth-OV: Towards Training-Free Open-Vocabulary Segmentation for Remote Sensing Images


SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model


SegFace: Face Segmentation of Long-Tail Classes


SegFlow: Joint Learning for Video Object Segmentation and Optical Flow


SegForestNet: Spatial-Partitioning-Based Aerial Image Segmentation


SegGroup: Seg-Level Supervision for 3D Instance and Semantic Segmentation


SegHist: A General Segmentation-based Framework for Chinese Historical Document Text Line Detection


SegImgNet: Segmentation-Guided Dual-Branch Network for Retinal Disease Diagnoses


SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies


SegLocNet: Multimodal Localization Network for Autonomous Driving via Bird's-Eye-View Segmentation


SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation


SegMobaTree: The Segmented Multilayer Online Balanced Tree for high-performance IPv6 Lookup in the Edge Network


SegNBDT: Visual Decision Rules for Segmentation


SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation


SegNet4D: Efficient Instance-Aware 4D Semantic Segmentation for LiDAR Point Cloud


SegPrompt: Boosting Open-world Segmentation via Category-level Prompt Learning


SegRCDB: Semantic Segmentation via Formula-Driven Supervised Learning


SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma


SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process


SegReg: Segmenting OARs by Registering MR Images and CT Annotations


SegRet: An Efficient Design for Semantic Segmentation with Retentive Network


SegStitch: Multidimensional Transformer for Robust and Efficient Medical Imaging Segmentation


SegSub: Evaluating Robustness to Knowledge Conflicts and Hallucinations in Vision-Language Models


SegTransVAE: Hybrid CNN -- Transformer with Regularization for medical image segmentation


SegVG: Transferring Object Bounding Box to Segmentation for Visual Grounding


SegX: Improving Interpretability of Clinical Image Diagnosis with Segmentation-based Enhancement


Segatron: Segment-Aware Transformer for Language Modeling and Understanding


SegmATRon: Embodied Adaptive Semantic Segmentation for Indoor Environment


Segment Aggregation for short utterances speaker verification using raw waveforms


Segment Any Mesh: Zero-shot Mesh Part Segmentation via Lifting Segment Anything 2 to 3D


Segment Any Point Cloud Sequences by Distilling Vision Foundation Models


Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation


Segment Anything Model for Road Network Graph Extraction


Segment Anything Model for Zero-shot Single Particle Tracking in Liquid Phase Transmission Electron Microscopy


Segment Anything Model is a Good Teacher for Local Feature Learning


Segment Anything for Satellite Imagery: A Strong Baseline and a Regional Dataset for Automatic Field Delineation


Segment Anything for Videos: A Systematic Survey


Segment Anything in 3D with Radiance Fields


Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting


Segment Anything with Multiple Modalities


Segment Change Model (SCM) for Unsupervised Change detection in VHR Remote Sensing Images: a Case Study of Buildings


Segment Every Out-of-Distribution Object


Segment First or Comprehend First? Explore the Limit of Unsupervised Word Segmentation with Large Language Models


Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language Models


Segment Routing: a Comprehensive Survey of Research Activities, Standardization Efforts and Implementation Results


Segment This Thing: Foveated Tokenization for Efficient Point-Prompted Segmentation


Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection


Segment anything model (SAM) for brain extraction in fMRI studies


Segment anything model for head and neck tumor segmentation with CT, PET and MRI multi-modality images


Segment as You Wish -- Free-Form Language-Based Segmentation for Medical Images


Segment, Select, Correct: A Framework for Weakly-Supervised Referring Segmentation


Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations


Segment-Anything Models Achieve Zero-shot Robustness in Autonomous Driving


Segment-Based Attention Masking for GPTs


Segment-Based Formal Verification of WiFi Fragmentation and Power Save Mode


SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI


SegmentAnything helps microscopy images based automatic and quantitative organoid detection and analysis


Segmentation Ability Map: Interpret deep features for medical image segmentation


Segmentation Consistency Training: Out-of-Distribution Generalization for Medical Image Segmentation


Segmentation Dataset for Reinforced Concrete Construction


Segmentation Fault: A Cheap Defense Against Adversarial Machine Learning


Segmentation Mask Guided End-to-End Person Search


Segmentation Style Discovery: Application to Skin Lesion Images


Segmentation and Generation of Magnetic Resonance Images by Deep Neural Networks


Segmentation and Smoothing Affect Explanation Quality More Than the Choice of Perturbation-based XAI Method for Image Explanations


Segmentation and Tracking of Vegetable Plants by Exploiting Vegetable Shape Feature for Precision Spray of Agricultural Robots


Segmentation by registration-enabled SAM prompt engineering using five reference images


Segmentation from Natural Language Expressions


Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP


Segmentation method for cerebral blood vessels from MRA using hysteresis


Segmentation of Anatomical Layers and Artifacts in Intravascular Polarization Sensitive Optical Coherence Tomography Using Attending Physician and Boundary Cardinality Losses


Segmentation of Blood Vessels, Optic Disc Localization, Detection of Exudates and Diabetic Retinopathy Diagnosis from Digital Fundus Images


Segmentation of Brain MRI using an Altruistic Harris Hawks' Optimization algorithm


Segmentation of Brain Metastases in MRI: A Two-Stage Deep Learning Approach with Modality Impact Study


Segmentation of EM showers for neutrino experiments with deep graph neural networks


Segmentation of MRI head anatomy using deep volumetric networks and multiple spatial priors


Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?


Segmentation of Non-Small Cell Lung Carcinomas: Introducing DRU-Net and Multi-Lens Distortion


Segmentation of Scanning Tunneling Microscopy Images Using Variational Methods and Empirical Wavelets


Segmentation of arbitrary features in very high resolution remote sensing imagery


Segmentation of coronal holes in solar disk images with a convolutional neural network


Segmentation of turbulent computational fluid dynamics simulations with unsupervised ensemble learning


Segmentation with Noisy Labels via Spatially Correlated Distributions


Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape Features


Segmentation with mixed supervision: Confidence maximization helps knowledge distillation


Segmentation, Classification, and Quality Assessment of UW-OCTA Images for the Diagnosis of Diabetic Retinopathy


Segmentation-Aware Convolutional Networks Using Local Attention Masks


Segmentation-Aware Generative Reinforcement Network (GRN) for Tissue Layer Segmentation in 3-D Ultrasound Images for Chronic Low-back Pain (cLBP) Assessment


Segmentation-Consistent Probabilistic Lesion Counting


Segmentation-Free Outcome Prediction from Head and Neck Cancer PET/CT Images: Deep Learning-Based Feature Extraction from Multi-Angle Maximum Intensity Projections (MA-MIPs)


Segmentation-Free Streaming Machine Translation


Segmentation-driven 6D Object Pose Estimation


Segmentation-free integration of nuclei morphology and spatial transcriptomics for retinal images


Segmentation-guided Layer-wise Image Vectorization with Gradient Fills


Segmentation-guided MRI reconstruction for meaningfully diverse reconstructions


Segmentations-Leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation


Segmented Learning for Class-of-Service Network Traffic Classification


Segmented Pairwise Distance for Time Series with Large Discontinuities


Segmenting Medical Images with Limited Data


Segmenting Moving Objects via an Object-Centric Layered Representation


Segmenting Transparent Object in the Wild with Transformer


Segmenting Transparent Objects in the Wild


Segmenting Unseen Industrial Components in a Heavy Clutter Using RGB-D Fusion and Synthetic Data


Segmenting Watermarked Texts From Language Models


Segmenting mechanically heterogeneous domains via unsupervised learning


Segmenting root systems in X-ray computed tomography images using level sets


Segmenting two-dimensional structures with strided tensor networks


Segregator: Global Point Cloud Registration with Semantic and Geometric Cues


Seis2Rock: A Data-Driven Approach to Direct Petrophysical Inversion of Pre-Stack Seismic Data


SeisCLIP: A seismology foundation model pre-trained by multi-modal data for multi-purpose seismic feature extraction


SeisFusion: Constrained Diffusion Model with Input Guidance for 3D Seismic Data Interpolation and Reconstruction


SeisMoLLM: Advancing Seismic Monitoring via Cross-modal Transfer with Pre-trained Large Language Model


SeisT: A foundational deep learning model for earthquake monitoring tasks


Seismic Data Strong Noise Attenuation Based on Diffusion Model and Principal Component Analysis


Seismic Foundation Model (SFM): a new generation deep learning model in geophysics


Seismic Traveltime Tomography with Label-free Learning


Seismic-ionospheric disturbances in ionospheric TEC and plasma parameters associated with the 14 July 2019 Mw 7.2 Laiwui earthquake detected by the GPS and CSES


SeizeIT2: Wearable Dataset Of Patients With Focal Epilepsy


Seizing Opportunity: Maintenance Optimization in Offshore Wind Farms Considering Accessibility, Production, and Crew Dispatch


Seizure Detection and Prediction by Parallel Memristive Convolutional Neural Networks


SeizureTransformer: Scaling U-Net with Transformer for Simultaneous Time-Step Level Seizure Detection from Long EEG Recordings


Sejong Face Database: A Multi-Modal Disguise Face Database


SelECT-SQL: Self-correcting ensemble Chain-of-Thought for Text-to-SQL


SelF-Eval: Self-supervised Fine-grained Dialogue Evaluation


SelFlow: Self-Supervised Learning of Optical Flow


SelQA: A New Benchmark for Selection-based Question Answering


SelaFD:Seamless Adaptation of Vision Transformer Fine-tuning for Radar-based Human Activity


Seldom: An Anonymity Network with Selective Deanonymization


SelecMix: Debiased Learning by Contradicting-pair Sampling


Select Wisely and Explain: Active Learning and Probabilistic Local Post-hoc Explainability


Select and Attend: Towards Controllable Content Selection in Text Generation


Select and Summarize: Scene Saliency for Movie Script Summarization


Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement Learning


Select, Read, and Write: A Multi-Agent Framework of Full-Text-based Related Work Generation


Select, Substitute, Search: A New Benchmark for Knowledge-Augmented Visual Question Answering


Select-Additive Learning: Improving Generalization in Multimodal Sentiment Analysis


Select-Mosaic: Data Augmentation Method for Dense Small Object Scenes


SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection


SelectLLM: Can LLMs Select Important Instructions to Annotate?


SelectNAdapt: Support Set Selection for Few-Shot Domain Adaptation


Selected Languages are All You Need for Cross-lingual Truthfulness Transfer


Selecting ChIP-seq Normalization Methods from the Perspective of their Technical Conditions


Selecting Demonstrations for Many-Shot In-Context Learning via Gradient Matching


Selecting Features by their Resilience to the Curse of Dimensionality


Selecting Features for Markov Modeling: A Case Study on HP35


Selecting Models based on the Risk of Damage Caused by Adversarial Attacks


Selecting Optimal Candidate Profiles in Adversarial Environments Using Conjoint Analysis and Machine Learning


Selecting Parallel In-domain Sentences for Neural Machine Translation Using Monolingual Texts


Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification


Selecting Relevant Structural Features for Glassy Dynamics by Information Imbalance


Selecting Representative Examples for Program Synthesis


Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery


Selecting Stickers in Open-Domain Dialogue through Multitask Learning


Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models


Selecting and combining complementary feature representations and classifiers for hate speech detection


Selecting and scheduling an optimal subset of road network upgrades


Selecting efficient and reliable preservation strategies: modeling long-term information integrity using large-scale hierarchical discrete event simulation


Selecting invalid instruments to improve Mendelian randomization with two-sample summary data


Selecting the Best Sequential Transfer Path for Medical Image Segmentation with Limited Labeled Data


Selecting the Most Conflicting Pair of Candidates


Selecting the Number of Clusters $K$ with a Stability Trade-off: an Internal Validation Criterion


Selecting the best compositions of a wheelchair basketball team: a data-driven approach


Selecting the motion ground truth for loose-fitting wearables: benchmarking optical MoCap methods


Selecting the number of components in PCA via random signflips


Selection Bias Induced Spurious Correlations in Large Language Models


Selection Collider Bias in Large Language Models


Selection Functions in Astronomical Data Modeling, with the Space Density of White Dwarfs as Worked Example


Selection Heuristics on Semantic Genetic Programming for Classification Problems


Selection by Prediction with Conformal p-values


Selection for short-term empowerment accelerates the evolution of homeostatic neural cellular automata


Selection from Hierarchical Data with Conformal e-values


Selection models with monotone weight functions in meta analysis


Selection of Regression Models under Linear Restrictions for Fixed and Random Designs


Selection via Proxy: Efficient Data Selection for Deep Learning


Selection-based Question Answering of an MOOC


SelectionConv: Convolutional Neural Networks for Non-rectilinear Image Data


Selective "Selective Prediction": Reducing Unnecessary Abstention in Vision-Language Reasoning


Selective Aggregation for Low-Rank Adaptation in Federated Learning


Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models


Selective Annotation Makes Language Models Better Few-Shot Learners


Selective Attention Merging for low resource tasks: A case study of Child ASR


Selective Attention for Context-aware Neural Machine Translation


Selective Attention: Enhancing Transformer through Principled Context Control


Selective Classification Under Distribution Shifts


Selective Classification via One-Sided Prediction


Selective Clustering Annotated using Modes of Projections


Selective Demonstrations for Cross-domain Text-to-SQL


Selective Differential Privacy for Language Modeling


Selective Exploration and Information Gathering in Search and Rescue Using Hierarchical Learning Guided by Natural Language Input


Selective Fairness in Recommendation via Prompts


Selective Generation for Controllable Language Models


Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model


Selective Inference for Changepoint detection by Recurrent Neural Network


Selective Information Passing for MR/CT Image Segmentation


Selective Knowledge Distillation for Neural Machine Translation


Selective Light Field Refocusing for Camera Arrays Using Bokeh Rendering and Superresolution


Selective Listening by Synchronizing Speech with Lips


Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives


Selective Network Linearization for Efficient Private Inference


Selective Noise Suppression Methods Using Random SVPWM to Shape the Noise Spectrum of PMSMs


Selective Parallel Loading of Large-Scale Compressed Graphs with ParaGrapher


Selective Pre-training for Private Fine-tuning


Selective Prompt Anchoring for Code Generation


Selective Prompting Tuning for Personalized Conversations with LLMs


Selective Regression Under Fairness Criteria


Selective Replay Enhances Learning in Online Continual Analogical Reasoning


Selective Residual M-Net for Real Image Denoising


Selective Spatio-Temporal Aggregation Based Pose Refinement System: Towards Understanding Human Activities in Real-World Videos


Selective Task Group Updates for Multi-Task Optimization


Selective Test-Time Adaptation for Unsupervised Anomaly Detection using Neural Implicit Representations


Selective Text Augmentation with Word Roles for Low-Resource Text Classification


Selective Token Generation for Few-shot Natural Language Generation