Data Contamination: From Memorization to Exploitation


Data Correction and Evolution Analysis of the ProgrammableWeb Service Ecosystem


Data Curation Alone Can Stabilize In-context Learning


Data Curation and Quality Assurance for Machine Learning-based Cyber Intrusion Detection


Data Defenses Against Large Language Models


Data Depth and Core-based Trend Detection on Blockchain Transaction Networks


Data Detection in Large Multi-Antenna Wireless Systems via Approximate Semidefinite Relaxation


Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)


Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation?


Data Discovery for the SDGs: A Systematic Rule-based Approach


Data Distillation for Text Classification


Data Distribution Distilled Generative Model for Generalized Zero-Shot Recognition


Data Diversification: A Simple Strategy For Neural Machine Translation


Data Driven Environmental Awareness Using Wireless Signals


Data Driven VRP: A Neural Network Model to Learn Hidden Preferences for VRP


Data Efficient 3D Learner via Knowledge Transferred from 2D Model


Data Efficient Contrastive Learning in Histopathology using Active Sampling


Data Efficient Language-supervised Zero-shot Recognition with Optimal Transport Distillation


Data Efficient Masked Language Modeling for Vision and Language


Data Efficient Stagewise Knowledge Distillation


Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images


Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention


Data Encoding for VQC in Qiskit, A Comparison With Novel Hybrid Encoding


Data Engineering for Data Analytics: A Classification of the Issues, and Case Studies


Data Engineering for Scaling Language Models to 128K Context


Data Factors for Better Compositional Generalization


Data Feedback Loops: Model-driven Amplification of Dataset Biases


Data Freshness in Mixed-Memory Intermittently-Powered Systems


Data Fusion for Audiovisual Speaker Localization: Extending Dynamic Stream Weights to the Spatial Domain


Data Fusion for Deep Learning on Transport Mode Detection: A Case Study


Data Fusion for Heterogeneous Treatment Effect Estimation with Multi-Task Gaussian Processes


Data Fusion for Multi-Task Learning of Building Extraction and Height Estimation


Data Fusion of Synthetic Query Variants With Generative Large Language Models


Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data


Data Generation Scheme for Thermal Modality with Edge-Guided Adversarial Conditional Diffusion Model


Data Generation as Sequential Decision Making


Data Generation for Post-OCR correction of Cyrillic handwriting


Data Generation-based Operator Learning for Solving Partial Differential Equations on Unbounded Domains


Data Harmonization Via Regularized Nonparametric Mixing Distribution Estimation


Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT


Data Hunches: Incorporating Personal Knowledge into Visualizations


Data Imbalance, Uncertainty Quantification, and Generalization via Transfer Learning in Data-driven Parameterizations: Lessons from the Emulation of Gravity Wave Momentum Transport in WACCM


Data Imputation by Pursuing Better Classification: A Supervised Kernel-Based Method


Data Imputation for Sparse Radio Maps in Indoor Positioning (Extended Version)


Data Imputation from the Perspective of Graph Dirichlet Energy


Data Imputation with Iterative Graph Reconstruction


Data Integration Via Analysis of Subspaces (DIVAS)


Data Integration with Fusion Searchlight: Classifying Brain States from Resting-state fMRI


Data Leakage and Evaluation Issues in Micro-Expression Analysis


Data Leakage in Notebooks: Static Detection and Better Processes


Data Level Lottery Ticket Hypothesis for Vision Transformers


Data Lifecycle Management in Evolving Input Distributions for Learning-based Aerospace Applications


Data Management For Training Large Language Models: A Survey


Data Mapping and Finite Difference Learning


Data Matters: The Case of Predicting Mobile Cellular Traffic


Data Mesh: a Systematic Gray Literature Review


Data Mining in Clinical Trial Text: Transformers for Classification and Question Answering Tasks


Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance


Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data?


Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework


Data Modelling for the Evaluation of Virtualized Network Functions Resource Allocation Algorithms


Data Models for Dataset Drift Controls in Machine Learning With Optical Images


Data Movement Is All You Need: A Case Study on Optimizing Transformers


Data Navigator: An accessibility-centered data navigation toolkit


Data Optimization in Deep Learning: A Survey


Data Origin Inference in Machine Learning


Data Point Selection for Line Chart Visualization: Methodological Assessment and Evidence-Based Guidelines


Data Poisoning Attacks Against Federated Learning Systems


Data Poisoning Attacks Against Multimodal Encoders


Data Poisoning Attacks to Locally Differentially Private Frequent Itemset Mining Protocols


Data Poisoning Won't Save You From Facial Recognition


Data Poisoning in Deep Learning: A Survey


Data Poisoning in LLMs: Jailbreak-Tuning and Scaling Laws


Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets


Data Preparation for Software Vulnerability Prediction: A Systematic Literature Review


Data Privacy Vocabulary (DPV) -- Version 2


Data Programming using Continuous and Quality-Guided Labeling Functions


Data Proportion Detection for Optimized Data Management for Large Language Models


Data Pruning Can Do More: A Comprehensive Data Pruning Approach for Object Re-identification


Data Pruning in Generative Diffusion Models


Data Quality Matters For Adversarial Training: An Empirical Study


Data Quality Measures and Efficient Evaluation Algorithms for Large-Scale High-Dimensional Data


Data Race Detection on Compressed Traces


Data Recombination for Neural Semantic Parsing


Data Reduction Pipeline for the MMT and Magellan Infrared Spectrograph


Data Rejuvenation: Exploiting Inactive Training Examples for Neural Machine Translation


Data Release 1 of the Dark Energy Spectroscopic Instrument


Data Representations' Study of Latent Image Manifolds


Data Roaming and Quality Assessment for Composed Image Retrieval


Data Scaling Laws in Imitation Learning for Robotic Manipulation


Data Scaling in OBDA Benchmarks: The VIG Approach


Data Science Education in Undergraduate Physics: Lessons Learned from a Community of Practice


Data Science Principles for Interpretable and Explainable AI


Data Segmentation via t-SNE, DBSCAN, and Random Forest


Data Selection for Fine-tuning Large Language Models Using Transferred Shapley Values


Data Selection for Language Models via Importance Resampling


Data Services with Bindaas: RESTful Interfaces for Diverse Data Sources


Data Shapley: Equitable Valuation of Data for Machine Learning


Data Sharing and Compression for Cooperative Networked Control


Data Similarity is Not Enough to Explain Language Model Performance


Data Space Inversion for Efficient Predictions and Uncertainty Quantification for Geothermal Models


Data Subsampling for Bayesian Neural Networks


Data Upcycling Knowledge Distillation for Image Super-Resolution


Data Valuation Without Training of a Model


Data Valuation from Data-Driven Optimization


Data Valuation using Neural Networks for Efficient Instruction Fine-Tuning


Data Visceralization: Enabling Deeper Understanding of Data Using Virtual Reality


Data Watermarking for Sequential Recommender Systems


Data Whisperer: Efficient Data Selection for Task-Specific LLM Fine-Tuning via Few-Shot In-Context Learning


Data and Knowledge Co-driving for Cancer Subtype Classification on Multi-Scale Histopathological Slides


Data and Representation for Turkish Natural Language Inference


Data and models for stance and premise detection in COVID-19 tweets: insights from the Social Media Mining for Health (SMM4H) 2022 shared task


Data assimilation in Agent-based models using creation and annihilation operators


Data assimilation with agent-based models using Markov chain sampling


Data augmentation for learning predictive models on EEG: a systematic comparison


Data augmentation on graphs for table type classification


Data augmentation on-the-fly and active learning in data stream classification


Data augmentation through multivariate scenario forecasting in Data Centers using Generative Adversarial Networks


Data augmentation using prosody and false starts to recognize non-native children's speech


Data discovery of low dimensional fluid dynamics of turbulent flows


Data driven approach towards more efficient Newton-Raphson power flow calculation for distribution grids


Data driven discovery of human mobility models


Data driven localized wave solution of the Fokas-Lenells equation using modified PINN


Data driven modeling for self-similar dynamics


Data embedding and prediction by sparse tropical matrix factorization


Data fusion of complementary data sources using Machine Learning enables higher accuracy Solar Resource Maps


Data integration methods for micro-randomized trials


Data integration of non-probability and probability samples with predictive mean matching


Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework


Data mining techniques on astronomical spectra data. I : Clustering Analysis


Data mining techniques on astronomical spectra data. II : Classification Analysis


Data mining, dashboard and statistical analysis: a powerful framework for the chemical design of molecular nanomagnets


Data preprocessing to mitigate bias: A maximum entropy based approach


Data re-uploading for a universal quantum classifier


Data recovery in computational fluid dynamics through deep image priors


Data segmentation based on the local intrinsic dimension


Data selection method for assessment of autonomous vehicles


Data set creation and empirical analysis for detecting signs of depression from social media postings


Data sharing in the metaverse with key abuse resistance based on decentralized CP-ABE


Data subsampling for Poisson regression with pth-root-link


Data to Controller for Nonlinear Systems: An Approximate Solution


Data transformation based optimized customer churn prediction model for the telecommunication industry


Data types as a more ergonomic frontend for Grammar-Guided Genetic Programming


Data valuation: The partial ordinal Shapley value for machine learning


Data-Adaptive Automatic Threshold Calibration for Stability Selection


Data-Adaptive Discriminative Feature Localization with Statistically Guaranteed Interpretation


Data-Adaptive Graph Framelets with Generalized Vanishing Moments for Graph Signal Processing


Data-Adaptive Identification of Effect Modifiers through Stochastic Shift Interventions and Cross-Validated Targeted Learning


Data-Adaptive Tradeoffs among Multiple Risks in Distribution-Free Prediction


Data-Agnostic Augmentations for Unknown Variations: Out-of-Distribution Generalisation in MRI Segmentation


Data-Agnostic Cardinality Learning from Imperfect Workloads


Data-Agnostic Robotic Long-Horizon Manipulation with Vision-Language-Guided Closed-Loop Feedback


Data-Augmentation for Graph Neural Network Learning of the Relaxed Energies of Unrelaxed Structures


Data-Augmentation-Based Dialectal Adaptation for LLMs


Data-Aware Training Quality Monitoring and Certification for Reliable Deep Learning


Data-Centric AI Paradigm Based on Application-Driven Fine-Grained Dataset Design


Data-Centric Approach to Constrained Machine Learning: A Case Study on Conway's Game of Life


Data-Centric Evolution in Autonomous Driving: A Comprehensive Survey of Big Data System, Data Mining, and Closed-Loop Technologies


Data-Centric Foundation Models in Computational Healthcare: A Survey


Data-Centric Green AI: An Exploratory Empirical Study


Data-Centric Human Preference Optimization with Rationales


Data-Centric Label Smoothing for Explainable Glaucoma Screening from Eye Fundus Images


Data-Centric Learning from Unlabeled Graphs with Diffusion Model


Data-Centric Strategies for Overcoming PET/CT Heterogeneity: Insights from the AutoPET III Lesion Segmentation Challenge


Data-Constrained Solar Modeling with GX Simulator


Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow


Data-Dependence of Plateau Phenomenon in Learning with Neural Network --- Statistical Mechanical Analysis


Data-Driven 3D Reconstruction of Dressed Humans From Sparse Views


Data-Driven Approach for Log Instruction Quality Assessment


Data-Driven Approximation of Stationary Nonlinear Filters with Optimal Transport Maps


Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals


Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes


Data-Driven Computational Imaging for Scientific Discovery


Data-Driven Control of Positive Linear Systems using Linear Programming


Data-Driven Copy-Paste Imputation for Energy Time Series


Data-Driven Denoising of Stationary Accelerometer Signals


Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes


Data-Driven Distributionally Robust Optimal Control with State-Dependent Noise


Data-Driven Distributionally Robust Optimal Power Flow for Distribution Systems


Data-Driven Equation Discovery of a Cloud Cover Parameterization


Data-Driven Falsification of Cyber-Physical Systems


Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series


Data-Driven High-Dimensional Statistical Inference with Generative Models


Data-Driven Information Extraction and Enrichment of Molecular Profiling Data for Cancer Cell Lines


Data-Driven Intersection Management Solutions for Mixed Traffic of Human-Driven and Connected and Automated Vehicles


Data-Driven Latency Probability Prediction for Wireless Networks: Focusing on Tail Probabilities


Data-Driven Law Firm Rankings to Reduce Information Asymmetry in Legal Disputes


Data-Driven Learning of 3-Point Correlation Functions as Microstructure Representations


Data-Driven Linearization of Dynamical Systems


Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling


Data-Driven Mirror Descent with Input-Convex Neural Networks


Data-Driven Modeling of IRCU Patient Flow in the COVID-19 Pandemic


Data-Driven Modeling of Noise Time Series with Convolutional Generative Adversarial Networks


Data-Driven Modeling of S0 -> S1 Excitation Energy in the BODIPY Chemical Space: High-Throughput Computation, Quantum Machine Learning, and Inverse Design


Data-Driven Modeling of Telluric Features and Stellar Variability with StellarSpectraObservationFitting.jl


Data-Driven Models for Traffic Flow at Junctions


Data-Driven Molecular Dynamics and TEM Analysis of Crystal Growth and Hydrogen Sensing in Pt-Functionalized Graphene Chemiresistive Sensors


Data-Driven Multi-Grid Solver for Accelerated Pressure Projection


Data-Driven Network Neuroscience: On Data Collection and Benchmark


Data-Driven Neuron Allocation for Scale Aggregation Networks


Data-Driven Nonconvex Reachability Analysis using Exact Multiplication


Data-Driven Nonlinear Deformation Design of 3D-Printable Shells


Data-Driven Observability Analysis for Nonlinear Stochastic Systems


Data-Driven Occupancy Grid Mapping using Synthetic and Real-World Data


Data-Driven Offline Optimization For Architecting Hardware Accelerators


Data-Driven Optimization of Directed Information over Discrete Alphabets


Data-Driven Output Prediction and Control of Stochastic Systems: An Innovation-Based Approach


Data-Driven Parametrization of Molecular Mechanics Force Fields for Expansive Chemical Space Coverage


Data-Driven Performance Guarantees for Classical and Learned Optimizers


Data-Driven Prediction of Route-Level Energy Use for Mixed-Vehicle Transit Fleets


Data-Driven Prediction of Seismic Intensity Distributions Featuring Hybrid Classification-Regression Models


Data-Driven Priors in the Maximum Entropy on the Mean Method for Linear Inverse Problems


Data-Driven Probabilistic Air-Sea Flux Parameterization


Data-Driven Random Projection and Screening for High-Dimensional Generalized Linear Models


Data-Driven Robot Fault Detection and Diagnosis Using Generative Models: A Modified SFDD Algorithm


Data-Driven Robust Backward Reachable Sets for Set-Theoretic Model Predictive Control


Data-Driven Robust Optimization using Unsupervised Deep Learning


Data-Driven Safety Verification using Barrier Certificates and Matrix Zonotopes


Data-Driven Sample Average Approximation with Covariate Information


Data-Driven Scenario Optimization for Automated Controller Tuning with Probabilistic Performance Guarantees


Data-Driven Score-Based Models for Generating Stable Structures with Adaptive Crystal Cells


Data-Driven Screening of Network Constraints for Unit Commitment


Data-Driven Self-Supervised Graph Representation Learning


Data-Driven Sensor Fault Diagnosis with Proven Guarantees using Incrementally Stable Recurrent Neural Networks


Data-Driven Set-Based Estimation using Matrix Zonotopes with Set Containment Guarantees


Data-Driven Simulator for Mechanical Circulatory Support with Domain Adversarial Neural Process


Data-Driven Socio-Economic Deprivation Prediction via Dimensionality Reduction: The Power of Diffusion Maps


Data-Driven Spectral Submanifold Reduction for Nonlinear Optimal Control of High-Dimensional Robots


Data-Driven Stabilization of Periodic Orbits


Data-Driven Structured Policy Iteration for Homogeneous Distributed Systems


Data-Driven Subgroup Identification for Linear Regression


Data-Driven Synthesis of Smoke Flows with CNN-based Feature Descriptors


Data-Driven System Identification of Quadrotors Subject to Motor Delays


Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration


Data-Driven Uncertainty Quantification of the Wave-Telescope Technique: General Equations and Application to HelioSwarm


Data-Driven and Stealthy Deactivation of Safety Filters


Data-Driven, Physics-Informed Descriptors of Cation Ordering in Multicomponent Oxides


Data-Driven, Soft Alignment of Functional Data Using Shapes and Landmarks


Data-Efficient Augmentation for Training Neural Networks


Data-Efficient Classification of Birdcall Through Convolutional Neural Networks Transfer Learning


Data-Efficient Classification of Radio Galaxies


Data-Efficient Collaborative Decentralized Thermal-Inertial Odometry


Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity


Data-Efficient Deep Learning Method for Image Classification Using Data Augmentation, Focal Cosine Loss, and Ensemble


Data-Efficient Deep Reinforcement Learning for Attitude Control of Fixed-Wing UAVs: Field Experiments


Data-Efficient Double-Win Lottery Tickets from Robust Pre-training


Data-Efficient Finetuning Using Cross-Task Nearest Neighbors


Data-Efficient Graph Grammar Learning for Molecular Generation


Data-Efficient Image Quality Assessment with Attention-Panel Decoder


Data-Efficient Instance Generation from Instance Discrimination


Data-Efficient Learning with Neural Programs


Data-Efficient Limited-Angle CT Using Deep Priors and Regularization


Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge


Data-Efficient Model Learning for Control with Jacobian-Regularized Dynamic-Mode Decomposition}


Data-Efficient Molecular Generation with Hierarchical Textual Inversion


Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning


Data-Efficient Reinforcement Learning with Self-Predictive Representations


Data-Efficient Sleep Staging with Synthetic Time Series Pretraining


Data-Efficient Strategies for Expanding Hate Speech Detection into Under-Resourced Languages


Data-Efficient Structured Pruning via Submodular Optimization


Data-Efficient Training of CNNs and Transformers with Coresets: A Stability Perspective


Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images


Data-Error Scaling in Machine Learning on Natural Discrete Combinatorial Mutation-prone Sets: Case Studies on Peptides and Small Molecules


Data-Free Backbone Fine-Tuning for Pruned Neural Networks


Data-Free Class-Incremental Gesture Recognition with Prototype-Guided Pseudo Feature Replay


Data-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning in Machine Learning Model Market


Data-Free Generalized Zero-Shot Learning


Data-Free Hard-Label Robustness Stealing Attack


Data-Free Learning of Reduced-Order Kinematics


Data-Free Universal Attack by Exploiting the Intrinsic Vulnerability of Deep Models


Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equations


Data-Independent Operator: A Training-Free Artifact Representation Extractor for Generalizable Deepfake Detection


Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection


Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value


Data-Oriented Language Implementation of Lattice-Boltzmann Method for Dense and Sparse Geometries


Data-SUITE: Data-centric identification of in-distribution incongruous examples


Data-access performance anti-patterns in data-intensive systems


Data-analysis software framework 2DMAT and its application to experimental measurements for two-dimensional material structures


Data-assisted reduced-order modeling of extreme events in complex dynamical systems


Data-assisted, physics-informed propagators for recurrent flows


Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-$β$ signaling


Data-centric Prediction Explanation via Kernelized Stein Discrepancy


Data-centric online ecosystem for digital materials science


Data-conforming data-driven control: avoiding premature generalizations beyond data


Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation


Data-driven Aerodynamic Analysis of Structures using Gaussian Processes


Data-driven Aeroelastic Analyses of Structures in Turbulent Wind Conditions using Enhanced Gaussian Processes with Aerodynamic Priors


Data-driven Analysis of T-Product-based Dynamical Systems


Data-driven Approach for Interpolation of Sparse Data


Data-driven Approach for Quality Evaluation on Knowledge Sharing Platform


Data-driven Construction of Hierarchical Matrices with Nested Bases


Data-driven Control of T-Product-based Dynamical Systems


Data-driven Control of Unknown Linear Systems via Quantized Feedback


Data-driven Coreference-based Ontology Building


Data-driven Crop Growth Simulation on Time-varying Generated Images using Multi-conditional Generative Adversarial Networks


Data-driven Design of Context-aware Monitors for Hazard Prediction in Artificial Pancreas Systems


Data-driven Discovery of Cyber-Physical Systems


Data-driven Discovery of Invariant Measures


Data-driven Distributionally Robust Control Based on Sinkhorn Ambiguity Sets


Data-driven Forced Oscillation Localization using Inferred Impulse Responses


Data-driven Global Ocean Modeling for Seasonal to Decadal Prediction


Data-driven Hi2Lo for Coarse-grid System Thermal Hydraulic Modeling


Data-driven Inverse Optimization with Imperfect Information


Data-driven Knowledge Fusion for Deep Multi-instance Learning


Data-driven Koopman Operators for Model-based Shared Control of Human-Machine Systems


Data-driven Linear Quadratic Tracking based Temperature Control of a Big Area Additive Manufacturing System


Data-driven Loop Closure Detection in Bathymetric Point Clouds for Underwater SLAM


Data-driven Meta-set Based Fine-Grained Visual Classification


Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation


Data-driven Model Predictive Control using MATLAB


Data-driven Modeling of the Mechanical Behavior of Anisotropic Soft Biological Tissue


Data-driven Mutation Analysis for Cyber-Physical Systems


Data-driven Output-feedback Predictive Control: Unknown Plant's Order and Measurement Noise


Data-driven Parsing Evaluation for Child-Parent Interactions


Data-driven Perception of Neuron Point Process with Unknown Unknowns


Data-driven Precipitation Nowcasting Using Satellite Imagery


Data-driven Prior Learning for Bayesian Optimisation


Data-driven Regularization via Racecar Training for Generalizing Neural Networks


Data-driven Super-Resolution of Flood Inundation Maps using Synthetic Simulations


Data-driven Tensor Train Gradient Cross Approximation for Hamilton-Jacobi-Bellman Equations


Data-driven Tissue Mechanics with Polyconvex Neural Ordinary Differential Equations


Data-driven Viscosity Solver for Fluid Simulation


Data-driven adjoint-based calibration of port-Hamiltonian systems in time domain


Data-driven and constrained optimization of semi-local exchange and non-local correlation functionals for materials and surface chemistry


Data-driven anisotropic finite viscoelasticity using neural ordinary differential equations


Data-driven approach for diagnostic analysis of dynamic bottlenecks in serial manufacturing systems


Data-driven approach for modeling Reynolds stress tensor with invariance preservation


Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data


Data-driven approaches for predicting spread of infectious diseases through DINNs: Disease Informed Neural Networks


Data-driven classification of low-power communication signals by an unauthenticated user using a software-defined radio


Data-driven cold starting of good reservoirs


Data-driven control of switched linear systems with probabilistic stability guarantees


Data-driven decision-focused surrogate modeling


Data-driven derivation of stellar properties from photometric time series data using convolutional neural networks


Data-driven detrending of nonstationary fractal time series with echo state networks


Data-driven discovery of Koopman eigenfunctions for control


Data-driven discovery of dynamics from time-resolved coherent scattering


Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation


Data-driven discovery of intrinsic dynamics


Data-driven discovery of multiscale chemical reactions governed by the law of mass action


Data-driven discovery of self-similarity using neural networks


Data-driven distributionally robust MPC using the Wasserstein metric


Data-driven effective model shows a liquid-like deep learning


Data-driven emotional body language generation for social robotics


Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta


Data-driven generation of spatio-temporal routines in human mobility


Data-driven identification of latent port-Hamiltonian systems


Data-driven interdiction with asymmetric cost uncertainty: a distributionally robust optimization approach


Data-driven micromobility network planning for demand and safety


Data-driven model reduction of agent-based systems using the Koopman generator


Data-driven modeling reveals a universal dynamic underlying the COVID-19 pandemic under social distancing


Data-driven optimal control of a SEIR model for COVID-19


Data-driven optimal control with neural network modeling of gradient flows


Data-driven optimization of processes with degrading equipment


Data-driven physics-based modeling of pedestrian dynamics


Data-driven plasma modelling: Surrogate collisional radiative models of fluorocarbon plasmas from deep generative autoencoders


Data-driven polynomial ridge approximation using variable projection


Data-driven quark and gluon jet modification in heavy-ion collisions


Data-driven rainfall prediction at a regional scale: a case study with Ghana


Data-driven reconstruction of spectral conductivity and chemical potential from thermoelectric transport data


Data-driven reduced modeling of streamer discharges in air


Data-driven reduced order models using invariant foliations, manifolds and autoencoders


Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshots


Data-driven solutions of ill-posed inverse problems arising from doping reconstruction in semiconductors


Data-driven stabilizations of goodness-of-fit tests


Data-driven strategies for optimal bicycle network growth


Data-driven study of composition-dependent phase compatibility in NiTi shape memory alloys


Data-driven subgrouping of patient trajectories with chronic diseases: Evidence from low back pain


Data-driven synchronization-avoiding algorithms in the explicit distributed structural analysis of soft tissue


Data-efficient Alignment of Multimodal Sequences by Aligning Gradient Updates and Internal Feature Distributions


Data-efficient Fine-tuning for LLM-based Recommendation


Data-efficient Large Vision Models through Sequential Autoregression


Data-efficient and Interpretable Inverse Materials Design using a Disentangled Variational Autoencoder


Data-efficient generation of protein conformational ensembles with backbone-to-side chain transformers


Data-free Backdoor Removal based on Channel Lipschitzness


Data-free Defense of Black Box Models Against Adversarial Attacks


Data-free Knowledge Distillation for Fine-grained Visual Categorization


Data-free Universal Adversarial Perturbation with Pseudo-semantic Prior


Data-independent Module-aware Pruning for Hierarchical Vision Transformers


Data-proximal null-space networks for inverse problems


Data-specific Adaptive Threshold for Face Recognition and Authentication


Data-to-Dashboard: Multi-Agent LLM Framework for Insightful Visualization in Enterprise Analytics


Data-to-Model Distillation: Data-Efficient Learning Framework


Data-to-Text Generation with Iterative Text Editing


Data-to-Text Generation with Style Imitation


Data-to-text Generation by Splicing Together Nearest Neighbors


Data-to-text Generation for Severely Under-Resourced Languages with GPT-3.5: A Bit of Help Needed from Google Translate


Data-to-text Generation with Macro Planning


Data-to-text Generation with Variational Sequential Planning


Data2Neo - A Tool for Complex Neo4j Data Integration


Data@Hand: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction


DataBright: Towards a Global Exchange for Decentralized Data Ownership and Trusted Computation


DataCLUE: A Benchmark Suite for Data-centric NLP


DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization


DataDAM: Efficient Dataset Distillation with Attention Matching


DataDock: An Open Source Data Hub for Research


DataDream: Few-shot Guided Dataset Generation


DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows


DataElixir: Purifying Poisoned Dataset to Mitigate Backdoor Attacks via Diffusion Models


DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback


DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions


DataLearner: A Data Mining and Knowledge Discovery Tool for Android Smartphones and Tablets


DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation


DataLight: Offline Data-Driven Traffic Signal Control


DataMUX: Data Multiplexing for Neural Networks


DataMap: A Portable Application for Visualizing High-Dimensional Data


DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts


DataPerf: Benchmarks for Data-Centric AI Development


DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python


DataProVe: A Data Protection Policy and System Architecture Verification Tool


DataRec: A Python Library for Standardized and Reproducible Data Management in Recommender Systems


DataSciBench: An LLM Agent Benchmark for Data Science


DataSculpt: Crafting Data Landscapes for Long-Context LLMs through Multi-Objective Partitioning


DataStates-LLM: Lazy Asynchronous Checkpointing for Large Language Models


DataTales: A Benchmark for Real-World Intelligent Data Narration


DataVisT5: A Pre-trained Language Model for Jointly Understanding Text and Data Visualization


DataViz3D: An Novel Method Leveraging Online Holographic Modeling for Extensive Dataset Preprocessing and Visualization


DataZoo: Streamlining Traffic Classification Experiments


Database Design for SpExoDisks: A Database & Web Portal for Spectra of Exoplanet-Forming Disks


Database Reconstruction from Noisy Volumes: A Cache Side-Channel Attack on SQLite


Database development and exploration of microstructure versus process relationships using variational autoencoders


Database for identifiability properties of linear compartmental models


Datacube segmentation via Deep Spectral Clustering


Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection


Dataflow graphs as complete causal graphs


Dataflow-Guided Retrieval Augmentation for Repository-Level Code Completion


Dataless Knowledge Fusion by Merging Weights of Language Models


Datalog-based Scalable Semantic Diffing of Concurrent Programs


Dataset Artefacts are the Hidden Drivers of the Declining Disruptiveness in Science


Dataset Clustering for Improved Offline Policy Learning


Dataset Condensation Driven Machine Unlearning


Dataset Condensation for Time Series Classification via Dual Domain Matching


Dataset Condensation via Efficient Synthetic-Data Parameterization


Dataset Condensation with Contrastive Signals


Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum


Dataset Distillation by Automatic Training Trajectories


Dataset Distillation by Matching Training Trajectories


Dataset Distillation for Offline Reinforcement Learning


Dataset Distillation using Neural Feature Regression


Dataset Distillation via Adversarial Prediction Matching


Dataset Distillation via Committee Voting


Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks


Dataset Distillation via Vision-Language Category Prototype


Dataset Distillation with Convexified Implicit Gradients


Dataset Distillers Are Good Label Denoisers In the Wild


Dataset Enhancement with Instance-Level Augmentations


Dataset Generation Patterns for Evaluating Knowledge Graph Construction


Dataset Generation and Bonobo Classification from Weakly Labelled Videos


Dataset Inference: Ownership Resolution in Machine Learning


Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation


Dataset Knowledge Transfer for Class-Incremental Learning without Memory


Dataset Optimization Strategies for MalwareTraffic Detection


Dataset Ownership Verification in Contrastive Pre-trained Models


Dataset Quantization with Active Learning based Adaptive Sampling


Dataset Regeneration for Sequential Recommendation


Dataset Reset Policy Optimization for RLHF


Dataset Search In Biodiversity Research: Do Metadata In Data Repositories Reflect Scholarly Information Needs?


Dataset Structural Index: Leveraging a machine's perspective towards visual data


Dataset and Baseline System for Multi-lingual Extraction and Normalization of Temporal and Numerical Expressions


Dataset and Benchmark for Urdu Natural Scenes Text Detection, Recognition and Visual Question Answering


Dataset and Benchmark: Novel Sensors for Autonomous Vehicle Perception


Dataset and Case Studies for Visual Near-Duplicates Detection in the Context of Social Media


Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition


Dataset and Models for Item Recommendation Using Multi-Modal User Interactions


Dataset artefacts in anti-spoofing systems: a case study on the ASVspoof 2017 benchmark


Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigms


Dataset distillation for memorized data: Soft labels can leak held-out teacher knowledge


Dataset for Automatic Summarization of Russian News


Dataset for anomalies detection in 3D printing


Dataset for the First Evaluation on Chinese Machine Reading Comprehension


Dataset of Multi-aspect Integrated Migration Indicators


Dataset of Propaganda Techniques of the State-Sponsored Information Operation of the People's Republic of China


Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Types


Dataset of Tensile Properties for Sub-sized Specimens of Nuclear Structural Materials


Dataset of Video Game Development Problems


Dataset of an EEG-based BCI experiment in Virtual Reality and on a Personal Computer


Dataset2Vec: Learning Dataset Meta-Features


Dataset: Impact Events for Structural Health Monitoring of a Plastic Thin Plate


Dataset: Large-scale Urban IoT Activity Data for DDoS Attack Emulation


DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models


DatasetEquity: Are All Samples Created Equal? In The Quest For Equity Within Datasets


DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance Fields


Datasets and Models for Authorship Attribution on Italian Personal Writings


Datasets for Fairness in Language Models: An In-Depth Survey


Datasets for Large Language Models: A Comprehensive Survey


Datasets for Online Controlled Experiments


Datasets for Portuguese Legal Semantic Textual Similarity: Comparing weak supervision and an annotation process approaches


Datasets for Studying Generalization from Easy to Hard Examples


DatashareNetwork: A Decentralized Privacy-Preserving Search Engine for Investigative Journalists


Datasheet for Subjective and Objective Quality Assessment Datasets


Datasheets Aren't Enough: DataRubrics for Automated Quality Metrics and Accountability


Datasheets for AI and medical datasets (DAIMS): a data validation and documentation framework before machine learning analysis in medical research


Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models


Date Estimation in the Wild of Scanned Historical Photos: An Image Retrieval Approach


DateLogicQA: Benchmarking Temporal Biases in Large Language Models


Dated Data: Tracing Knowledge Cutoffs in Large Language Models


Dateformer: Time-modeling Transformer for Longer-term Series Forecasting


Dating Documents using Graph Convolution Networks


David and Goliath: An Empirical Evaluation of Attacks and Defenses for QNNs at the Deep Edge


Davydov-Yetter cohomology and relative homological algebra


DawDreamer: Bridging the Gap Between Digital Audio Workstations and Python Interfaces


Dawn of the transformer era in speech emotion recognition: closing the valence gap


DawnIK: Decentralized Collision-Aware Inverse Kinematics Solver for Heterogeneous Multi-Arm Systems


Day and Night: Habitability of Tidally Locked Planets with Sporadic Rotation


Day-to-Day Dynamic Traffic Assignment with Imperfect Information, Bounded Rationality and Information Sharing


Dcc --help: Generating Context-Aware Compiler Error Explanations with Large Language Models


De Novo Generation of Hit-like Molecules from Gene Expression Profiles via Deep Learning


De Novo Molecular Generation via Connection-aware Motif Mining


De novo Drug Design using Reinforcement Learning with Multiple GPT Agents


De novo PROTAC design using graph-based deep generative models


De novo reconstruction of satellite repeat units from sequence data


De-Biasing the Bias: Methods for Improving Disparity Assessments with Noisy Group Measurements


De-Confusing Pseudo-Labels in Source-Free Domain Adaptation


De-DSI: Decentralised Differentiable Search Index


De-Sequentialized Monte Carlo: a parallel-in-time particle smoother


De-biased Lasso for Generalized Linear Models with A Diverging Number of Covariates


De-biased lasso for stratified Cox models with application to the national kidney transplant data


De-biasing Distantly Supervised Named Entity Recognition via Causal Intervention


De-coupling and De-positioning Dense Self-supervised Learning


De-distorting ionospheric effects in the image plane


De-identification of Privacy-related Entities in Job Postings


De-jargonizing Science for Journalists with GPT-4: A Pilot Study


De-novo Identification of Small Molecules from Their GC-EI-MS Spectra


DeAR: Accelerating Distributed Deep Learning with Fine-Grained All-Reduce Pipelining


DeBaCl: A Python Package for Interactive DEnsity-BAsed CLustering


DeBayes: a Bayesian Method for Debiasing Network Embeddings


DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing Attention


DeC and ADER: Similarities, Differences and a Unified Framework


DeCLIP: Decoupled Learning for Open-Vocabulary Dense Perception


DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations


DeCaFlow: A Deconfounding Causal Generative Model


DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos


DeCap: Decoding CLIP Latents for Zero-Shot Captioning via Text-Only Training


DeCo: Decoupling Token Compression from Semantic Abstraction in Multimodal Large Language Models


DeCoDEx: Confounder Detector Guidance for Improved Diffusion-based Counterfactual Explanations


DeCoMa: Detecting and Purifying Code Dataset Watermarks through Dual Channel Code Abstraction


DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection


DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate Hallucinations


DeDUCE: Generating Counterfactual Explanations Efficiently


DeFINE: Delayed Feedback based Immersive Navigation Environment for Studying Goal-Directed Human Navigation


DeFTAN-II: Efficient Multichannel Speech Enhancement with Subgroup Processing


DeFactoNLP: Fact Verification using Entity Recognition, TFIDF Vector Comparison and Decomposable Attention


DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation Learning


DeFi Protocols for Loanable Funds: Interest Rates, Liquidity and Market Efficiency


DeFi Risk Transfer: Towards A Fully Decentralized Insurance Protocol


DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling


DeFoG: Discrete Flow Matching for Graph Generation


DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering


DeFraudNet:End2End Fingerprint Spoof Detection using Patch Level Attention


DeFusion: An Effective Decoupling Fusion Network for Multi-Modal Pregnancy Prediction


DeGPR: Deep Guided Posterior Regularization for Multi-Class Cell Detection and Counting


DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4


DeID-VC: Speaker De-identification via Zero-shot Pseudo Voice Conversion


DeIDClinic: A Multi-Layered Framework for De-identification of Clinical Free-text Data


DeInfoReg: A Decoupled Learning Framework for Better Training Throughput


DeL-haTE: A Deep Learning Tunable Ensemble for Hate Speech Detection


DeLF: Designing Learning Environments with Foundation Models


DeLTA-BIT: an open-source probabilistic tractography-based deep learning framework for thalamic targeting in functional neurological disorders


DeLoRes: Decorrelating Latent Spaces for Low-Resource Audio Representation Learning


DeMEtRIS: Counting (near)-Cliques by Crawling


DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting


DeMPT: Decoding-enhanced Multi-phase Prompt Tuning for Making LLMs Be Better Context-aware Translators


DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark


DeMem: Privacy-Enhanced Robust Adversarial Learning via De-Memorization


DeMo: Decoupled Feature-Based Mixture of Experts for Multi-Modal Object Re-Identification


DeNetDM: Debiasing by Network Depth Modulation


DeOcc-1-to-3: 3D De-Occlusion from a Single Image via Self-Supervised Multi-View Diffusion


DeOccNet: Learning to See Through Foreground Occlusions in Light Fields


DePA: Improving Non-autoregressive Machine Translation with Dependency-Aware Decoder


DePAint: A Decentralized Safe Multi-Agent Reinforcement Learning Algorithm considering Peak and Average Constraints


DeProPose: Deficiency-Proof 3D Human Pose Estimation via Adaptive Multi-View Fusion


DeRDaVa: Deletion-Robust Data Valuation for Machine Learning


DeRIS: Decoupling Perception and Cognition for Enhanced Referring Image Segmentation through Loopback Synergy


DeRO: Dead Reckoning Based on Radar Odometry With Accelerometers Aided for Robot Localization


DeRPN: Taking a further step toward more general object detection


DeS3: Adaptive Attention-driven Self and Soft Shadow Removal using ViT Similarity


DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation


DeSCo: Towards Generalizable and Scalable Deep Subgraph Counting


DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models


DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment


DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly Detection


DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision


DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal


DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking


DeSiRe-GS: 4D Street Gaussians for Static-Dynamic Decomposition and Surface Reconstruction for Urban Driving Scenes


DeSocial: Blockchain-based Decentralized Social Networks


DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms in Vision Transformers


DeTRAP: RISC-V Return Address Protection With Debug Triggers


DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning


DeText: A Deep Text Ranking Framework with BERT


DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLM


DeToxy: A Large-Scale Multimodal Dataset for Toxicity Classification in Spoken Utterances


DeVAn: Dense Video Annotation for Video-Language Models


DeVLBert: Learning Deconfounded Visio-Linguistic Representations


DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenes


DeViL: Decoding Vision features into Language


DeXTT: Deterministic Cross-Blockchain Token Transfers


Dead Pixel Test Using Effective Receptive Field


Dead or Alive: Continuous Data Profiling for Interactive Data Science


Dead or Murdered? Predicting Responsibility Perception in Femicide News Reports


Deadlock and Noise in Self-Organized Aggregation Without Computation


DealMVC: Dual Contrastive Calibration for Multi-view Clustering


Dealing With Heterogeneous 3D MR Knee Images: A Federated Few-Shot Learning Method With Dual Knowledge Distillation


Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification


Dealing with Abbreviations in the Slovenian Biographical Lexicon


Dealing with Cross-Task Class Discrimination in Online Continual Learning


Dealing with Expert Bias in Collective Decision-Making


Dealing with Logs and Zeros in Regression Models


Dealing with Popularity Bias in Recommender Systems for Third-party Libraries: How far Are We?


Dealing with Semantic Underspecification in Multimodal NLP


Dealing with Synthetic Data Contamination in Online Continual Learning


Dealing with Typos for BERT-based Passage Retrieval and Ranking


Dealing with Unknown Unknowns: Identification and Selection of Minimal Sensing for Fractional Dynamics with Unknown Inputs


Dealing with inequality constraints in large-scale semidefinite relaxations for graph coloring and maximum clique problems


Dealing with missing data using attention and latent space regularization


Dealing with multiple intercurrent events using hypothetical and treatment policy strategies simultaneously


Dealing with uncertainty in agent-based models for short-term predictions


Dealing with uncertainty: balancing exploration and exploitation in deep recurrent reinforcement learning


Dear Sir or Madam, May I introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer


DebUnc: Improving Large Language Model Agent Communication With Uncertainty Metrics


Debatable Intelligence: Benchmarking LLM Judges via Debate Speech Evaluation


Debate Helps Supervise Unreliable Experts


DebateKG: Automatic Policy Debate Case Creation with Semantic Knowledge Graphs


DebateQA: Evaluating Question Answering on Debatable Knowledge


Debating with More Persuasive LLMs Leads to More Truthful Answers


Debatrix: Multi-dimensional Debate Judge with Iterative Chronological Analysis Based on LLM


DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks


Debiased Bayesian inference for average treatment effects


Debiased Collaborative Filtering with Kernel-Based Causal Balancing


Debiased Contrastive Learning for Sequential Recommendation


Debiased Contrastive Learning of Unsupervised Sentence Representations


Debiased Cross-modal Matching for Content-based Micro-video Background Music Recommendation


Debiased Explainable Pairwise Ranking from Implicit Feedback


Debiased Graph Poisoning Attack via Contrastive Surrogate Objective


Debiased Noise Editing on Foundation Models for Fair Medical Image Classification


Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics


Debiased Pairwise Learning from Positive-Unlabeled Implicit Feedback


Debiased Sample Selection for Combating Noisy Labels


Debiased Self-Training for Semi-Supervised Learning


Debiased inference for a covariate-adjusted regression function


Debiasify: Self-Distillation for Unsupervised Bias Mitigation


Debiasing 6-DOF IMU via Hierarchical Learning of Continuous Bias Dynamics


Debiasing Algorithm through Model Adaptation


Debiasing Cardiac Imaging with Controlled Latent Diffusion Models


Debiasing Evaluations That are Biased by Evaluations


Debiasing Functions of Private Statistics in Postprocessing


Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure


Debiasing Graph Transfer Learning via Item Semantic Clustering for Cross-Domain Recommendations


Debiasing Learning for Membership Inference Attacks Against Recommender Systems


Debiasing Made State-of-the-art: Revisiting the Simple Seed-based Weak Supervision for Text Classification


Debiasing Masks: A New Framework for Shortcut Mitigation in NLU


Debiasing Meta-Gradient Reinforcement Learning by Learning the Outer Value Function


Debiasing Methods in Natural Language Understanding Make Bias More Accessible


Debiasing Multilingual Word Embeddings: A Case Study of Three Indian Languages


Debiasing Multimodal Large Language Models


Debiasing Multimodal Large Language Models via Noise-Aware Preference Optimization


Debiasing Multimodal Models via Causal Information Minimization


Debiasing Pre-trained Contextualised Embeddings


Debiasing Recommendation by Learning Identifiable Latent Confounders


Debiasing Recommendation with Personal Popularity


Debiasing Sentence Embedders through Contrastive Word Pairs


Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure


Debiasing Skin Lesion Datasets and Models? Not So Fast


Debiasing Synthetic Data Generated by Deep Generative Models


Debiasing Text Safety Classifiers through a Fairness-Aware Ensemble


Debiasing Vision-Language Models via Biased Prompts


Debiasing Word Embeddings with Nonlinear Geometry


Debiasing a First-order Heuristic for Approximate Bi-level Optimization


Debiasing should be Good and Bad: Measuring the Consistency of Debiasing Techniques in Language Models


Debiasing the Cloze Task in Sequential Recommendation with Bidirectional Transformers


Debiasing the estimate of treatment effect on the treated with time-varying counfounders


Debiasing with Diffusion: Probabilistic reconstruction of Dark Matter fields from galaxies with CAMELS


Deblur-NeRF: Neural Radiance Fields from Blurry Images


Deblur4DGS: 4D Gaussian Splatting from Blurry Monocular Video


DeblurDiNAT: A Compact Model with Exceptional Generalization and Visual Fidelity on Unseen Domains


DeblurSR: Event-Based Motion Deblurring Under the Spiking Representation


Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks


Deblurring Photographs of Characters Using Deep Neural Networks


Deblurring galaxy images with Tikhonov regularization on magnitude domain


Debt-Financed Collateral and Stability Risks in the DeFi Ecosystem


DebtViz: A Tool for Identifying, Measuring, Visualizing, and Monitoring Self-Admitted Technical Debt


Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step


DebugBench: Evaluating Debugging Capability of Large Language Models


Debunking Fake News One Feature at a Time


Debunking the Myth of Join Ordering: Toward Robust SQL Analytics


DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases


DecAP: Decaying Action Priors for Accelerated Imitation Learning of Torque-Based Legged Locomotion Policies


DecETT: Accurate App Fingerprinting Under Encrypted Tunnels via Dual Decouple-based Semantic Enhancement


Decameter-sized Earth impactors -- I: Orbital properties


Decanus to Legatus: Synthetic training for 2D-3D human pose lifting


Decay No More: A Persistent Twitter Dataset for Learning Social Meaning


Decay Pruning Method: Smooth Pruning With a Self-Rectifying Procedure


Decay Replay Mining to Predict Next Process Events


Decay-Function-Free Time-Aware Attention to Context and Speaker Indicator for Spoken Language Understanding


Decaying Clipping Range in Proximal Policy Optimization


DeceFL: A Principled Decentralized Federated Learning Framework


Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data


Deceleration of high-velocity interstellar photon sails into bound orbits at $\alpha$ Centauri


Decentralised Moderation for Interoperable Social Networks: A Conversation-based Approach for Pleroma and the Fediverse


Decentralised construction of a global coordinate system in a large swarm of minimalistic robots


Decentralised, Collaborative, and Privacy-preserving Machine Learning for Multi-Hospital Data


Decentralization and Acceleration Enables Large-Scale Bundle Adjustment


Decentralization of Ethereum's Builder Market


Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies


Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models


Decentralized Baseband Processing for Massive MU-MIMO Systems


Decentralized Collaborative Inertial Tracking


Decentralized Collaborative Knowledge Management using Git


Decentralized Connectivity Control in Quadcopters: a Field Study of Communication Performance


Decentralized Cooperative Stochastic Bandits


Decentralized Cross-Blockchain Asset Transfers


Decentralized Deadlock-free Trajectory Planning for Quadrotor Swarm in Obstacle-rich Environments -- Extended version


Decentralized Deep Reinforcement Learning for a Distributed and Adaptive Locomotion Controller of a Hexapod Robot


Decentralized Energy Marketplace via NFTs and AI-based Agents


Decentralized Event-Triggered Federated Learning with Heterogeneous Communication Thresholds


Decentralized Federated Learning through Proxy Model Sharing


Decentralized Federated Policy Gradient with Byzantine Fault-Tolerance and Provably Fast Convergence


Decentralized Hyper-Gradient Computation over Time-Varying Directed Networks


Decentralized Intelligence in GameFi: Embodied AI Agents and the Convergence of DeFi and Virtual Ecosystems


Decentralized Kernel Ridge Regression Based on Data-Dependent Random Feature


Decentralized Low-Latency Collaborative Inference via Ensembles on the Edge


Decentralized Motion Planning for Multi-Robot Navigation using Deep Reinforcement Learning


Decentralized Multi-Agent Reinforcement Learning for Continuous-Space Stochastic Games


Decentralized Multi-Robot Navigation for Autonomous Surface Vehicles with Distributional Reinforcement Learning


Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization Collaborations


Decentralized Natural Policy Gradient with Variance Reduction for Collaborative Multi-Agent Reinforcement Learning


Decentralized Nonlinear Feedback Design with Separable Control Contraction Metrics


Decentralized Observer Design for Virtual Decomposition Control


Decentralized Online Ensembles of Gaussian Processes for Multi-Agent Systems


Decentralized Online Riemannian Optimization with Dynamic Environments


Decentralized Personalization for Federated Medical Image Segmentation via Gossip Contrastive Mutual Learning


Decentralized Personalized Federated Learning based on a Conditional Sparse-to-Sparser Scheme


Decentralized Planning for Car-Like Robotic Swarm in Cluttered Environments


Decentralized Power Allocation for MIMO-NOMA Vehicular Edge Computing Based on Deep Reinforcement Learning


Decentralized Predicate Detection over Partially Synchronous Continuous-Time Signals


Decentralized Quantum Federated Learning for Metaverse: Analysis, Design and Implementation


Decentralized Riemannian Gradient Descent on the Stiefel Manifold


Decentralized Robust Data-driven Predictive Control for Smoothing Mixed Traffic Flow


Decentralized SGD and Average-direction SAM are Asymptotically Equivalent


Decentralized Sensor Network Localization using Matrix-Parametrized Proximal Splittings


Decentralized Social Navigation with Non-Cooperative Robots via Bi-Level Optimization


Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees


Decentralized State Estimation In A Dimension-Reduced Linear Regression


Decentralized Statistical Inference with Unrolled Graph Neural Networks


Decentralized Strongly-Convex Optimization with Affine Constraints: Primal and Dual Approaches


Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning


Decentralized Training of Foundation Models in Heterogeneous Environments


Decentralized Unlabeled Multi-agent Pathfinding Via Target And Priority Swapping (With Supplementary)


Decentralized adaptive clustering of deep nets is beneficial for client collaboration


Decentralized and Robust Privacy-Preserving Model Using Blockchain-Enabled Federated Deep Learning in Intelligent Enterprises


Decentralized approaches for autonomous vehicles coordination


Decentralized learning with budgeted network load using Gaussian copulas and classifier ensembles


Decentralized optimization over noisy, rate-constrained networks: Achieving consensus by communicating differences


Decentralized optimization with affine constraints over time-varying networks


Decentralized optimization with non-identical sampling in presence of stragglers


Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling


Decentralized traffic management of autonomous drones


Decentralizing Custodial Wallets with MFKDF


Deceptive Fairness Attacks on Graphs via Meta Learning


Deceptive Game Design? Investigating the Impact of Visual Card Style on Player Perception


Deceptive Path Planning via Reinforcement Learning with Graph Neural Networks


Deceptive Semantic Shortcuts on Reasoning Chains: How Far Can Models Go without Hallucination?


DeciMamba: Exploring the Length Extrapolation Potential of Mamba


DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation


Decide less, communicate more: On the construct validity of end-to-end fact-checking in medicine


Decide: Knowledge-Based Version Incompatibility Detection in Deep Learning Stacks


Deciding Differential Privacy of Online Algorithms with Multiple Variables


Deciding How to Decide: Dynamic Routing in Artificial Neural Networks


Deciding Memory Safety for Single-Pass Heap-Manipulating Programs


Deciding Termination of Simple Randomized Loops


Decimated Framelet System on Graphs and Fast G-Framelet Transforms


Deciphering 'What' and 'Where' Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations


Deciphering Air Travel Disruptions: A Machine Learning Approach


Deciphering Bitcoin Blockchain Data by Cohort Analysis


Deciphering Compatibility Relationships with Textual Descriptions via Extraction and Explanation


Deciphering Cross-Modal Alignment in Large Vision-Language Models with Modality Integration Rate


Deciphering Environmental Air Pollution with Large Scale City Data


Deciphering Movement: Unified Trajectory Generation Model for Multi-Agent


Deciphering Oracle Bone Language with Diffusion Models


Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategies


Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective


Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees


Deciphering Textual Authenticity: A Generalized Strategy through the Lens of Large Language Semantics for Detecting Human vs. Machine-Generated Text


Deciphering Trajectory-Aided LLM Reasoning: An Optimization Perspective


Deciphering Undersegmented Ancient Scripts Using Phonetic Prior


Deciphering and integrating invariants for neural operator learning with various physical mechanisms


Deciphering public attention to geoengineering and climate issues using machine learning and dynamic analysis


Deciphering regulatory architectures from synthetic single-cell expression patterns


Deciphering the Chaos: Enhancing Jailbreak Attacks via Adversarial Prompt Translation


Deciphering the Enigma of Satellite Computing with COTS Devices: Measurement and Analysis


Deciphering the Factors Influencing the Efficacy of Chain-of-Thought: Probability, Memorization, and Noisy Reasoning


Deciphering the Interplay of Parametric and Non-parametric Memory in Retrieval-augmented Language Models


Deciphering the Language of Nature: A transformer-based language model for deleterious mutations in proteins


Deciphering the Role of Representation Disentanglement: Investigating Compositional Generalization in CLIP Models


Deciphering the Soliton-Halo Relation in Fuzzy Dark Matter


Deciphering the Underserved: Benchmarking LLM OCR for Low-Resource Scripts


Deciphering the imprint of topology on nonlinear dynamical network stability


Decipherment of Historical Manuscript Images


DecisioNet: A Binary-Tree Structured Neural Network


Decision Diagrams for Quantum Measurements with Shallow Circuits


Decision Information Meets Large Language Models: The Future of Explainable Operations Research


Decision Making in Non-Stationary Environments with Policy-Augmented Search


Decision Making under Cumulative Prospect Theory: An Alternating Direction Method of Multipliers


Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL


Decision Mamba: Reinforcement Learning via Sequence Modeling with Selective State Spaces


Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models


Decision Support System for Chronic Diseases Based on Drug-Drug Interactions


Decision Theory-Guided Deep Reinforcement Learning for Fast Learning


Decision Transformer under Random Frame Dropping


Decision Transformer vs. Decision Mamba: Analysing the Complexity of Sequential Decision Making in Atari Games


Decision Trees for Decision-Making under the Predict-then-Optimize Framework


Decision from Suboptimal Classifiers: Excess Risk Pre- and Post-Calibration


Decision support system for distributed manufacturing based on input-output analysis and economic complexity


Decision trees as partitioning machines to characterize their generalization properties


Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees


Decision-BADGE: Decision-based Adversarial Batch Attack with Directional Gradient Estimation


Decision-Dependent Stochastic Optimization: The Role of Distribution Dynamics


Decision-Focused Evaluation of Worst-Case Distribution Shift


Decision-Focused Forecasting: A Differentiable Multistage Optimisation Architecture


Decision-Focused Learning to Predict Action Costs for Planning


Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities


Decision-Focused Learning: Through the Lens of Learning to Rank


Decision-Making Under Uncertainty in Research Synthesis: Designing for the Garden of Forking Paths


Decision-Oriented Dialogue for Human-AI Collaboration


Decision-aware training of spatiotemporal forecasting models to select a top K subset of sites for intervention


Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal


Decision-based Universal Adversarial Attack


Decision-centric fairness: Evaluation and optimization for resource allocation problems


Decision-making and control with diffractive optical networks


Decision-oriented two-parameter Fisher information sensitivity using symplectic decomposition


DecisionHoldem: Safe Depth-Limited Solving With Diverse Opponents for Imperfect-Information Games


DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning


Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact Verification


Declaration-based Prompt Tuning for Visual Question Answering


Declarative Experimentation in Information Retrieval using PyTerrier


Declarative Knowledge Distillation from Large Language Models for Visual Question Answering Datasets


Decline Now: A Combinatorial Model for Algorithmic Collective Action


DecoPrompt : Decoding Prompts Reduces Hallucinations when Large Language Models Meet False Premises


DecoR: Deconfounding Time Series with Robust Regression


Decodable and Sample Invariant Continuous Object Encoder


Decoder Decomposition for the Analysis of the Latent Space of Nonlinear Autoencoders With Wind-Tunnel Experimental Data


Decoder ensembling for learned latent geometries


Decoder-in-the-Loop: Genetic Optimization-based LDPC Code Design


Decoder-only Streaming Transformer for Simultaneous Translation


Decoding Across the Quantum LDPC Code Landscape


Decoding Attention from Gaze: A Benchmark Dataset and End-to-End Models


Decoding Cognitive Health Using Machine Learning: A Comprehensive Evaluation for Diagnosis of Significant Memory Concern


Decoding Concerns: Multi-label Classification of Vaccine Sentiments in Social Media


Decoding Covert Speech from EEG Using a Functional Areas Spatio-Temporal Transformer


Decoding Decoded: Understanding Hyperparameter Effects in Open-Ended Text Generation


Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks


Decoding Demographic un-fairness from Indian Names


Decoding EEG Rhythms During Action Observation, Motor Imagery, and Execution for Standing and Sitting


Decoding Emotions: A comprehensive Multilingual Study of Speech Models for Speech Emotion Recognition


Decoding Envelope and Frequency-Following EEG Responses to Continuous Speech Using Deep Neural Networks


Decoding Generic Visual Representations From Human Brain Activity using Machine Learning


Decoding High-Order Interleaved Rank-Metric Codes


Decoding Human Attentive States from Spatial-temporal EEG Patches Using Transformers


Decoding MIE: A Novel Dataset Approach Using Topic Extraction and Affiliation Parsing


Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation


Decoding Memes: A Comparative Study of Machine Learning Models for Template Identification


Decoding Multilingual Moral Preferences: Unveiling LLM's Biases Through the Moral Machine Experiment


Decoding Natural Images from EEG for Object Recognition


Decoding Non-Linearity and Complexity: Deep Tabular Learning Approaches for Materials Science


Decoding Phone Pairs from MEG Signals Across Speech Modalities


Decoding Reading Goals from Eye Movements


Decoding Reed-Muller Codes with Successive Codeword Permutations


Decoding Single Molecule Time Traces with Dynamic Disorder


Decoding Social Sentiment in DAO: A Comparative Analysis of Blockchain Governance Communities


Decoding Urban Industrial Complexity: Enhancing Knowledge-Driven Insights via IndustryScopeGPT


Decoding Vision Transformers: the Diffusion Steering Lens


Decoding Visual Experience and Mapping Semantics through Whole-Brain Analysis Using fMRI Foundation Models


Decoding a Neural Retriever's Latent Space for Query Suggestion


Decoding by Contrasting Knowledge: Enhancing LLMs' Confidence on Edited Facts


Decoding fMRI Data into Captions using Prefix Language Modeling


Decoding fairness: a reinforcement learning perspective


Decoding finger velocity from cortical spike trains with recurrent spiking neural networks


Decoding natural image stimuli from fMRI data with a surface-based convolutional network


Decoding the Echoes of Vision from fMRI: Memory Disentangling for Past Semantic Information


Decoding the End-to-end Writing Trajectory in Scholarly Manuscripts


Decoding the Enigma: Benchmarking Humans and AIs on the Many Facets of Working Memory


Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks


Decoding the Secrets of Machine Learning in Malware Classification: A Deep Dive into Datasets, Feature Extraction, and Model Performance


Decoding the Silent Majority: Inducing Belief Augmented Social Graph with Large Language Model for Response Forecasting


Decoding the Style and Bias of Song Lyrics


Decoding the Underlying Meaning of Multimodal Hateful Memes


Decoding the Workplace & EOR: An Employee Survey Analysis by Data Science Techniques and Visualization


Decoding the relationship between domain structure and functionality in ferroelectrics via hidden latent variables


Decoding visual brain representations from electroencephalography through Knowledge Distillation and latent diffusion models


Decoding with Limited Teacher Supervision Requires Understanding When to Trust the Teacher


Decoherence of electron spin qubit during transfer between two semiconductor quantum dots at low magnetic fields


Decohering Tensor Network Quantum Machine Learning Models


Decolonising Data Systems: Using Jyutping or Pinyin as tonal representations of Chinese names for data linkage


DecomCAM: Advancing Beyond Saliency Maps through Decomposition and Integration


DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design


DecompEval: Evaluating Generated Texts as Unsupervised Decomposed Question Answering


DecompX: Explaining Transformers Decisions by Propagating Token Decomposition


DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios


Decomposable-Net: Scalable Low-Rank Compression for Neural Networks


Decompose and Leverage Preferences from Expert Models for Improving Trustworthiness of MLLMs


Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement


Decompose-ToM: Enhancing Theory of Mind Reasoning in Large Language Models through Simulation and Task Decomposition


Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation


Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems


Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics


Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning


Decomposed Prompt Tuning via Low-Rank Reparameterization


Decomposed Prompting for Machine Translation Between Related Languages using Large Language Models


Decomposed Prompting: A Modular Approach for Solving Complex Tasks


Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot Learning


Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation


Decomposing Control Lyapunov Functions for Efficient Reinforcement Learning


Decomposing Elements of Problem Solving: What "Math" Does RL Teach?


Decomposing Gaussians with Unknown Covariance


Decomposing Global Feature Effects Based on Feature Interactions


Decomposing Infrared Luminosity Functions into Star-Forming and AGN Components using CIGALE


Decomposing MLP Activations into Interpretable Features via Semi-Nonnegative Matrix Factorization


Decomposing Multiparameter Persistence Modules


Decomposing Natural Logic Inferences in Neural NLI


Decomposing The Dark Matter of Sparse Autoencoders


Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling


Decomposing abelian varieties into simple factors: algorithms and applications


Decomposing and Editing Predictions by Modeling Model Computation


Decomposing and Interpreting Image Representations via Text in ViTs Beyond CLIP


Decomposing conditional independence ideals with hidden variables


Decomposing dense matrices into dense Pauli tensors


Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models


Decomposing geographical and universal aspects of human mobility


Decomposing non-stationary signals with time-varying wave-shape functions


Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem Proving


Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection


Decomposition Based Refinement for the Network Interdiction Problem


Decomposition Betters Tracking Everything Everywhere


Decomposition Methods with Deep Corrections for Reinforcement Learning


Decomposition Pipeline for Large-Scale Portfolio Optimization with Applications to Near-Term Quantum Computing


Decomposition Strategies and Multi-shot ASP Solving for Job-shop Scheduling


Decomposition Strategies for Constructive Preference Elicitation


Decomposition and Adaptive Sampling for Data-Driven Inverse Linear Optimization


Decomposition and Modeling in the Non-Manifold domain


Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm


Decomposition of Higher-Order Spectra for Blind Multiple-Input Deconvolution, Pattern Identification and Separation


Decomposition of Longitudinal Deformations via Beltrami Descriptors


Decomposition of Neural Discrete Representations for Large-Scale 3D Mapping


Decomposition of Sparse Amplitude Permutation Gates with Application to Preparation of Sparse Clustered Quantum States


Decomposition of Water Demand Patterns Using Skewed Gaussian Distributions for Behavioral Insights and Operational Planning


Decomposition of stellar populations in CosmoDC2 galaxies using SCARLET and Deep Learning


Decomposition of unitary matrix into quantum gates


Decomposition with Monotone B-splines: Fitting and Testing


Decompositional Generation Process for Instance-Dependent Partial Label Learning


Decompounding discrete distributions: A non-parametric Bayesian approach


Decompressing Knowledge Graph Representations for Link Prediction


Deconditional Downscaling with Gaussian Processes


Deconfined Global Types for Asynchronous Sessions


Deconfounded Causal Collaborative Filtering


Deconfounded Recommendation for Alleviating Bias Amplification


Deconfounded Representation Similarity for Comparison of Neural Networks


Deconfounded Video Moment Retrieval with Causal Intervention


Deconfounding Actor-Critic Network with Policy Adaptation for Dynamic Treatment Regimes


Deconfounding Imitation Learning with Variational Inference


Deconfounding Legal Judgment Prediction for European Court of Human Rights Cases Towards Better Alignment with Experts


Deconfounding Reinforcement Learning in Observational Settings


Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies


Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces


Deconstructed Generation-Based Zero-Shot Model


Deconstructing Distributions: A Pointwise Framework of Learning


Deconstructing In-Context Learning: Understanding Prompts via Corruption


Deconstructing Long Chain-of-Thought: A Structured Reasoning Optimization Framework for Long CoT Distillation


Deconstructing equivariant representations in molecular systems


Deconstructing the Goldilocks Zone of Neural Network Initialization


Deconstructing the Inductive Biases of Hamiltonian Neural Networks


Decontextualized learning for interpretable hierarchical representations of visual patterns


Deconver: A Deconvolutional Network for Medical Image Segmentation


Deconvolution-Based Global Decoding for Neural Machine Translation


Deconvolutional Density Network: Modeling Free-Form Conditional Distributions


Decorated Merge Trees for Persistent Topology


Decorrelated Clustering with Data Selection Bias


Decorrelated Local Linear Estimator: Inference for Non-linear Effects in High-dimensional Additive Models


Decorrelation with conditional normalizing flows


Decorrelative Network Architecture for Robust Electrocardiogram Classification


Decouple Graph Neural Networks: Train Multiple Simple GNNs Simultaneously Instead of One


Decouple Learning for Parameterized Image Operators


DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation


Decoupled Appearance and Motion Learning for Efficient Anomaly Detection in Surveillance Video


Decoupled Competitive Framework for Semi-supervised Medical Image Segmentation


Decoupled Contrastive Learning for Long-Tailed Recognition


Decoupled Contrastive Multi-View Clustering with High-Order Random Walks


Decoupled Data Consistency with Diffusion Purification for Image Restoration


Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs


Decoupled Graph Neural Networks for Large Dynamic Graphs


Decoupled Iterative Refinement Framework for Interacting Hands Reconstruction from a Single RGB Image


Decoupled Knowledge with Ensemble Learning for Online Distillation


Decoupled Learning for Conditional Adversarial Networks


Decoupled Local Aggregation for Point Cloud Learning


Decoupled Mixup for Generalized Visual Recognition


Decoupled Multimodal Distilling for Emotion Recognition


Decoupled Rationalization with Asymmetric Learning Rates: A Flexible Lipschitz Restraint


Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder


Decoupled Self Attention for Accurate One Stage Object Detection


Decoupled Side Information Fusion for Sequential Recommendation


Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action Recognition


Decoupled Spatial-Temporal Transformer for Video Inpainting


Decoupled Variational Embedding for Signed Directed Networks


Decoupled Visual Interpretation and Linguistic Reasoning for Math Problem Solving


Decoupled and Memory-Reinforced Networks: Towards Effective Feature Learning for One-Step Person Search


Decoupled conditional contrastive learning with variable metadata for prostate lesion detection


Decoupling "when to update" from "how to update"


Decoupling Common and Unique Representations for Multimodal Self-supervised Learning


Decoupling Content and Expression: Two-Dimensional Detection of AI-Generated Text


Decoupling Degradations with Recurrent Network for Video Restoration in Under-Display Camera


Decoupling Dynamic Monocular Videos for Dynamic View Synthesis


Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices


Decoupling Exploration and Exploitation for Unsupervised Pre-training with Successor Features


Decoupling Feature Representations of Ego and Other Modalities for Incomplete Multi-modal Brain Tumor Segmentation


Decoupling Fine Detail and Global Geometry for Compressed Depth Map Super-Resolution


Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-Rank Decomposition


Decoupling Inherent Risk and Early Cancer Signs in Image-based Breast Cancer Risk Models


Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning


Decoupling Local and Global Representations of Time Series


Decoupling Magnitude and Phase Estimation with Deep ResUNet for Music Source Separation


Decoupling Makes Weakly Supervised Local Feature Better


Decoupling Meta-Reinforcement Learning with Gaussian Task Contexts and Skills


Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks


Decoupling Predictions in Distributed Learning for Multi-Center Left Atrial MRI Segmentation


Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery


Decoupling Semantic Context and Color Correlation with multi-class cross branch regularization


Decoupling Semantic Similarity from Spatial Alignment for Neural Networks


Decoupling Shrinkage and Selection in Gaussian Linear Factor Analysis


Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation


Decoupling Strategy and Generation in Negotiation Dialogues


Decoupling Structure and Lexicon for Zero-Shot Semantic Parsing


Decoupling Value and Policy for Generalization in Reinforcement Learning


Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks


Decoupling Zero-Shot Semantic Segmentation


Decoupling for fractal subsets of the parabola


Decoupling regularization from the action space


Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers


Decreasing Annotation Burden of Pairwise Comparisons with Human-in-the-Loop Sorting: Application in Medical Image Artifact Rating


Decreasing market value of variable renewables can be avoided by policy action


Decreasing the size of the Restricted Boltzmann machine


Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLP


Dedicated Restricted Target Wake Time for Real-Time Applications in Wi-Fi 7


Deductive Beam Search: Decoding Deducible Rationale for Chain-of-Thought Reasoning


Deductive Optimization of Relational Data Storage


Deductive Verification of Chain-of-Thought Reasoning


Deductive semiparametric estimation in Double-Sampling Designs with application to PEPFAR


Deduplicator: When Computation Reuse Meets Load Balancing at the Network Edge


DeeCLIP: A Robust and Generalizable Transformer-Based Framework for Detecting AI-Generated Images


DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable Diffusion


DeeLeMa: Missing information search with Deep Learning for Mass estimation


DeePKS-kit: a package for developing machine learning-based chemically accurate energy and density functional models


DeePMD-kit v2: A software package for Deep Potential models


DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer Transcriptome


DeePoly: A High-Order Accuracy Scientific Machine Learning Framework for Function Approximation and Solving PDEs


DeePore: a deep learning workflow for rapid and comprehensive characterization of porous materials


DeeProb-kit: a Python Library for Deep Probabilistic Modelling


DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution


Deemon: Detecting CSRF with Dynamic Analysis and Property Graphs


Deep 1D-Convnet for accurate Parkinson disease detection and severity prediction from gait


Deep 3D Vessel Segmentation based on Cross Transformer Network


Deep Active Alignment of Knowledge Graph Entities and Schemata


Deep Active Audio Feature Learning in Resource-Constrained Environments


Deep Active Inference Agents for Delayed and Long-Horizon Environments


Deep Active Inference for Partially Observable MDPs


Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem


Deep Active Learning Approach to Adaptive Beamforming for mmWave Initial Alignment


Deep Active Learning for Anchor User Prediction


Deep Active Learning for Axon-Myelin Segmentation on Histology Data


Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision


Deep Active Learning for Joint Classification & Segmentation with Weak Annotator


Deep Active Learning in Remote Sensing for data efficient Change Detection


Deep Active Learning via Open Set Recognition


Deep Active Learning with Adaptive Acquisition


Deep Active Learning with a Neural Architecture Search


Deep Active Learning: Unified and Principled Method for Query and Training


Deep Actor-Critic Learning for Distributed Power Control in Wireless Mobile Networks


Deep Adaptive Arbitrary Polynomial Chaos Expansion: A Mini-data-driven Semi-supervised Method for Uncertainty Quantification


Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design


Deep Adaptive Inference Networks for Single Image Super-Resolution


Deep Adaptive Multi-Intention Inverse Reinforcement Learning


Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images


Deep Affinity Network for Multiple Object Tracking


Deep Affordance Foresight: Planning Through What Can Be Done in the Future


Deep Age-Invariant Fingerprint Segmentation System


Deep Amended Gradient Descent for Efficient Spectral Reconstruction from Single RGB Images


Deep Amortized Inference for Probabilistic Programs


Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition


Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation


Deep Ancient Roman Republican Coin Classification via Feature Fusion and Attention


Deep Anomaly Detection under Labeling Budget Constraints


Deep Anomaly Detection with Outlier Exposure


Deep Architectures for Neural Machine Translation


Deep Atrous Guided Filter for Image Restoration in Under Display Cameras


Deep Attention Based Semi-Supervised 2D-Pose Estimation for Surgical Instruments


Deep Attention Driven Reinforcement Learning (DAD-RL) for Autonomous Decision-Making in Dynamic Environment


Deep Attention Q-Network for Personalized Treatment Recommendation


Deep Attention-guided Graph Clustering with Dual Self-supervision


Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound


Deep Autoencoders for Anomaly Detection in Textured Images using CW-SSIM


Deep Autoregressive Models with Spectral Attention


Deep Autotuner: a Pitch Correcting Network for Singing Performances


Deep Backtracking Counterfactuals for Causally Compliant Explanations


Deep Backward and Galerkin Methods for the Finite State Master Equation


Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks


Deep Bayesian Active Learning for Accelerating Stochastic Simulation


Deep Bayesian Active Learning for Preference Modeling in Large Language Models


Deep Bayesian Active Semi-Supervised Learning


Deep Bayesian Experimental Design for Quantum Many-Body Systems


Deep Bayesian Learning for Car Hacking Detection


Deep Bayesian Quadrature Policy Optimization


Deep Bayesian Unsupervised Lifelong Learning


Deep Bayesian inference for seismic imaging with tasks


Deep Bayesian segmentation for colon polyps: Well-calibrated predictions in medical imaging


Deep Belief Network based representation learning for lncRNA-disease association prediction


Deep Bidirectional Language-Knowledge Graph Pretraining


Deep Black-Box Reinforcement Learning with Movement Primitives


Deep Blind Super-Resolution for Satellite Video


Deep Boosting Learning: A Brand-new Cooperative Approach for Image-Text Matching


Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation


Deep CSI Compression for Dual-Polarized Massive MIMO Channels with Disentangled Representation Learning


Deep CSI Learning for Gait Biometric Sensing and Recognition


Deep Cascade Multi-task Learning for Slot Filling in Online Shopping Assistant


Deep Categorization with Semi-Supervised Self-Organizing Maps


Deep Causal Inference for Point-referenced Spatial Data with Continuous Treatments


Deep Channel Learning For Large Intelligent Surfaces Aided mm-Wave Massive MIMO Systems


Deep Class-Wise Hashing: Semantics-Preserving Hashing via Class-wise Loss


Deep Class-guided Hashing for Multi-label Cross-modal Retrieval


Deep Classifier Mimicry without Data Access


Deep Clustering Survival Machines with Interpretable Expert Distributions


Deep Clustering based Fair Outlier Detection


Deep Clustering for Data Cleaning and Integration


Deep Clustering of Tabular Data by Weighted Gaussian Distribution Learning


Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization


Deep Clustering with Diffused Sampling and Hardness-aware Self-distillation


Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach


Deep Clustering with Self-Supervision using Pairwise Similarities


Deep Clustering with a Dynamic Autoencoder: From Reconstruction towards Centroids Construction


Deep Co-Attention Network for Multi-View Subspace Learning


Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation


Deep Coarse-grained Potentials via Relative Entropy Minimization


Deep Coarse-to-fine Dense Light Field Reconstruction with Flexible Sampling and Geometry-aware Fusion


Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift


Deep Coded Aperture Design: An End-to-End Approach for Computational Imaging Tasks


Deep Collective Matrix Factorization for Augmented Multi-View Learning


Deep Common Feature Mining for Efficient Video Semantic Segmentation


Deep Completion Autoencoders for Radio Map Estimation


Deep Composer Classification Using Symbolic Representation


Deep Composite Face Image Attacks: Generation, Vulnerability and Detection


Deep Comprehensive Correlation Mining for Image Clustering


Deep Compressive Autoencoder for Action Potential Compression in Large-Scale Neural Recording


Deep Conditional Gaussian Mixture Model for Constrained Clustering


Deep Conditional Representation Learning for Drum Sample Retrieval by Vocalisation


Deep Confident Steps to New Pockets: Strategies for Docking Generalization


Deep Configuration Performance Learning: A Systematic Survey and Taxonomy


Deep Content Understanding Toward Entity and Aspect Target Sentiment Analysis on Foundation Models


Deep Contextual Clinical Prediction with Reverse Distillation


Deep Contextualized Self-training for Low Resource Dependency Parsing


Deep ContourFlow: Advancing Active Contours with Deep Learning


Deep ConvLSTM with self-attention for human activity decoding using wearables


Deep Convolutional Networks in System Identification


Deep Convolutional Neural Network Based Facial Expression Recognition in the Wild


Deep Convolutional Neural Network Design Patterns


Deep Convolutional Neural Networks for Palm Fruit Maturity Classification


Deep Convolutional Neural Networks with Zero-Padding: Feature Extraction and Learning


Deep Convolutional Pooling Transformer for Deepfake Detection


Deep Convolutional Ritz Method: Parametric PDE surrogates without labeled data


Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees


Deep Counterfactual Estimation with Categorical Background Variables


Deep Cox Mixtures for Survival Regression


Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution


Deep Data Augmentation for Weed Recognition Enhancement: A Diffusion Probabilistic Model and Transfer Learning Based Approach


Deep Data Consistency: a Fast and Robust Diffusion Model-based Solver for Inverse Problems


Deep Declarative Dynamic Time Warping for End-to-End Learning of Alignment Paths


Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks


Deep Decomposition Learning for Inverse Imaging Problems


Deep Deconfounded Content-based Tag Recommendation for UGC with Causal Intervention


Deep DeePC: Data-enabled predictive control with low or no online optimization using deep learning


Deep Defense: Training DNNs with Improved Adversarial Robustness


Deep Deformable 3D Caricatures with Learned Shape Control


Deep Demosaicing for Polarimetric Filter Array Cameras


Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds


Deep Depth Estimation from Thermal Image: Dataset, Benchmark, and Challenges


Deep Depth Estimation from Visual-Inertial SLAM


Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?


Deep Deterministic Independent Component Analysis for Hyperspectral Unmixing


Deep Deterministic Information Bottleneck with Matrix-based Entropy Functional


Deep Deterministic Portfolio Optimization


Deep Diacritization: Efficient Hierarchical Recurrence for Improved Arabic Diacritization


Deep Diffusion Processes for Active Learning of Hyperspectral Images


Deep Dimension Reduction for Supervised Representation Learning


Deep Directional Statistics: Pose Estimation with Uncertainty Quantification


Deep Directly-Trained Spiking Neural Networks for Object Detection


Deep Discrete Hashing with Self-supervised Pairwise Labels


Deep Discriminative Feature Learning for Accent Recognition


Deep Dive into the IoT Backend Ecosystem


Deep Diversity-Enhanced Feature Representation of Hyperspectral Images


Deep Domain Adaptation Regression for Force Calibration of Optical Tactile Sensors


Deep Domain Adaptation for Ordinal Regression of Pain Intensity Estimation Using Weakly-Labelled Videos


Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking Systems


Deep Double Descent via Smooth Interpolation


Deep Double Self-Expressive Subspace Clustering


Deep Dual Consecutive Network for Human Pose Estimation


Deep Dual Support Vector Data Description for Anomaly Detection on Attributed Networks


Deep Dynamic Probabilistic Canonical Correlation Analysis


Deep Dynamical Modeling and Control of Unsteady Fluid Flows


Deep EHR: Chronic Disease Prediction Using Medical Notes


Deep Efficient Continuous Manifold Learning for Time Series Modeling


Deep Efficient End-to-end Reconstruction (DEER) Network for Few-view Breast CT Image Reconstruction


Deep Embedded Clustering with Distribution Consistency Preservation for Attributed Networks


Deep Embedded Multi-view Clustering with Collaborative Training


Deep Emotion Recognition in Textual Conversations: A Survey


Deep Emotions Across Languages: A Novel Approach for Sentiment Propagation in Multilingual WordNets


Deep Empirical Risk Minimization in finance: looking into the future


Deep End-to-End Alignment and Refinement for Time-of-Flight RGB-D Module


Deep End-to-end Fingerprint Denoising and Inpainting


Deep Energy-Based Modeling of Discrete-Time Physics


Deep Enhanced Representation for Implicit Discourse Relation Recognition


Deep Ensemble Learning with Frame Skipping for Face Anti-Spoofing


Deep Ensemble Shape Calibration: Multi-Field Post-hoc Calibration in Online Advertising


Deep Ensemble of Weighted Viterbi Decoders for Tail-Biting Convolutional Codes


Deep Ensembles Work, But Are They Necessary?


Deep Ensembles for Graphs with Higher-order Dependencies


Deep Entity Matching with Pre-Trained Language Models


Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution


Deep Equals Shallow for ReLU Networks in Kernel Regimes


Deep Equilibrium Architectures for Inverse Problems in Imaging


Deep Equilibrium Diffusion Restoration with Parallel Sampling


Deep Equilibrium Learning of Explicit Regularizers for Imaging Inverse Problems


Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures


Deep Equilibrium Optical Flow Estimation


Deep Equilibrium models for Poisson Imaging Inverse problems via Mirror Descent


Deep EvoGraphNet Architecture For Time-Dependent Brain Graph Data Synthesis From a Single Timepoint


Deep Exogenous and Endogenous Influence Combination for Social Chatter Intensity Prediction


Deep Expander Networks: Efficient Deep Networks from Graph Theory


Deep Explicit Duration Switching Models for Time Series


Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning


Deep Extrapolation for Attribute-Enhanced Generation


Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark Estimation


Deep Fake Detection: Survey of Facial Manipulation Detection Solutions


Deep Fashion3D: A Dataset and Benchmark for 3D Garment Reconstruction from Single Images


Deep Feature Aggregation and Image Re-ranking with Heat Diffusion for Image Retrieval


Deep Feature Learning for Medical Acoustics


Deep Feature Response Discriminative Calibration


Deep Feature Selection using a Teacher-Student Network


Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification


Deep Feature Space: A Geometrical Perspective


Deep Feature Statistics Mapping for Generalized Screen Content Image Quality Assessment


Deep Federated Learning for Autonomous Driving


Deep Fidelity in DNN Watermarking: A Study of Backdoor Watermarking for Classification Models


Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning


Deep Finite Volume Method for Partial Differential Equations


Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting


Deep Forest: Neural Network reconstruction of the Lyman-alpha forest


Deep Fourier-embedded Network for Bi-modal Salient Object Detection


Deep Frank-Wolfe For Neural Network Optimization


Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions


Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization


Deep Fusion Prior for Plenoptic Super-Resolution All-in-Focus Imaging


Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimation


Deep Fusion of Local and Non-Local Features for Precision Landslide Recognition


Deep Fusion of Multi-Object Densities Using Transformer


Deep Gated Recurrent and Convolutional Network Hybrid Model for Univariate Time Series Classification


Deep Gaussian Denoiser Epistemic Uncertainty and Decoupled Dual-Attention Fusion


Deep Gaussian Process Priors for Bayesian Image Reconstruction


Deep Gaussian Processes for Air Quality Inference


Deep Gaussian Processes with Importance-Weighted Variational Inference


Deep Gaussian mixture model for unsupervised image segmentation


Deep Generalization of Structured Low-Rank Algorithms (Deep-SLR)