Towards Scale-Aware Low-Light Enhancement via Structure-Guided Transformer Design


Towards Scale-Aware, Robust, and Generalizable Unsupervised Monocular Depth Estimation by Integrating IMU Motion Dynamics


Towards Scaling Difference Target Propagation by Learning Backprop Targets


Towards Search-based Motion Planning for Micro Aerial Vehicles


Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems


Towards Secure and Practical Machine Learning via Secret Sharing and Random Permutation


Towards Secure and Usable 3D Assets: A Novel Framework for Automatic Visible Watermarking


Towards Self-Adaptive Machine Learning-Enabled Systems Through QoS-Aware Model Switching


Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs


Towards Self-Contained Answers: Entity-Based Answer Rewriting in Conversational Search


Towards Self-Explainable Graph Neural Network


Towards Self-Interpretable Graph-Level Anomaly Detection


Towards Self-Supervised Learning of Global and Object-Centric Representations


Towards Self-supervised and Weight-preserving Neural Architecture Search


Towards Semantic Consistency: Dirichlet Energy Driven Robust Multi-Modal Entity Alignment


Towards Semantic Fast-Forward and Stabilized Egocentric Videos


Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models


Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges


Towards Semantic Versioning of Open Pre-trained Language Model Releases on Hugging Face


Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin


Towards Semi-supervised Learning with Non-random Missing Labels


Towards Sequence-Level Training for Visual Tracking


Towards Signed Distance Function based Metamaterial Design: Neural Operator Transformer for Forward Prediction and Diffusion Model for Inverse Design


Towards Sim-to-Real Industrial Parts Classification with Synthetic Dataset


Towards Similarity Graphs Constructed by Deep Reinforcement Learning


Towards Single Camera Human 3D-Kinematics


Towards Single-Lens Controllable Depth-of-Field Imaging via Depth-Aware Point Spread Functions


Towards Size-Independent Generalization Bounds for Deep Operator Nets


Towards Small Object Editing: A Benchmark Dataset and A Training-Free Approach


Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction in A Triadic Interaction


Towards Solving the DeepFake Problem : An Analysis on Improving DeepFake Detection using Dynamic Face Augmentation


Towards Source Attribution of Singing Voice Deepfake with Multimodal Foundation Models


Towards Space-to-Ground Data Availability for Agriculture Monitoring


Towards Sparsification of Graph Neural Networks


Towards Spatial Transcriptomics-guided Pathological Image Recognition with Batch-Agnostic Encoder


Towards Spatio-Temporal Aware Traffic Time Series Forecasting--Full Version


Towards Speaker Identification with Minimal Dataset and Constrained Resources using 1D-Convolution Neural Network


Towards Specialized Wireless Networks Using an ML-Driven Radio Interface


Towards Speech Dialogue Translation Mediating Speakers of Different Languages


Towards Squeezing-Averse Virtual Try-On via Sequential Deformation


Towards Stability of Autoregressive Neural Operators


Towards Stabilizing Batch Statistics in Backward Propagation of Batch Normalization


Towards Stable Interstellar Flight: Levitation of a Laser-Propelled Sailcraft*


Towards Standardized Grid Emission Factors: Methodological Insights and Best Practices


Towards Standardized Mobility Reports with User-Level Privacy


Towards Stealthy Backdoor Attacks against Speech Recognition via Elements of Sound


Towards Stratified Space Learning: Linearly Embedded Graphs


Towards Structure-aware Model for Multi-modal Knowledge Graph Completion


Towards Student Actions in Classroom Scenes: New Dataset and Baseline


Towards Substructural Property-Based Testing


Towards Suicide Prevention from Bipolar Disorder with Temporal Symptom-Aware Multitask Learning


Towards Super-Resolution CEST MRI for Visualization of Small Structures


Towards Supervised Performance on Speaker Verification with Self-Supervised Learning by Leveraging Large-Scale ASR Models


Towards Supervised and Unsupervised Neural Machine Translation Baselines for Nigerian Pidgin


Towards Supporting Intelligence in 5G/6G Core Networks: NWDAF Implementation and Initial Analysis


Towards Surgical Context Inference and Translation to Gestures


Towards Sustainability of Systematic Literature Reviews


Towards Sustainable Learning: Coresets for Data-efficient Deep Learning


Towards Sustainable Self-supervised Learning


Towards Synchronous Memorizability and Generalizability with Site-Modulated Diffusion Replay for Cross-Site Continual Segmentation


Towards Syntactic Iberian Polarity Classification


Towards Synthetic Data Generation for Improved Pain Recognition in Videos under Patient Constraints


Towards Synthetic Magnetic Turbulence with Coherent Structures


Towards Systematic Monolingual NLP Surveys: GenA of Greek NLP


Towards Table-to-Text Generation with Pretrained Language Model: A Table Structure Understanding and Text Deliberating Approach


Towards Target-dependent Sentiment Classification in News Articles


Towards Task Sampler Learning for Meta-Learning


Towards Temporal Edge Regression: A Case Study on Agriculture Trade Between Nations


Towards Temporally Explainable Dysarthric Speech Clarity Assessment


Towards Test Generation from Task Description for Mobile Testing with Multi-modal Reasoning


Towards Text-Image Interleaved Retrieval


Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs


Towards Theoretically Inspired Neural Initialization Optimization


Towards Tight Convex Relaxations for Contact-Rich Manipulation


Towards Tokenized Human Dynamics Representation


Towards Top-Down Just Noticeable Difference Estimation of Natural Images


Towards Top-Down Stereo Image Quality Assessment via Stereo Attention


Towards Toxic and Narcotic Medication Detection with Rotated Object Detector


Towards Tracing Factual Knowledge in Language Models Back to the Training Data


Towards Tracing Trustworthiness Dynamics: Revisiting Pre-training Period of Large Language Models


Towards Training GNNs using Explanation Directed Message Passing


Towards Training Music Taggers on Synthetic Data


Towards Training Reproducible Deep Learning Models


Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion


Towards Training-free Anomaly Detection with Vision and Language Foundation Models


Towards Training-free Open-world Segmentation via Image Prompt Foundation Models


Towards Transactional Causal Consistent Microservices Business Logic


Towards Transferable Adversarial Attacks on Vision Transformers


Towards Transferable Targeted 3D Adversarial Attack in the Physical World


Towards Transmission-Friendly and Robust CNN Models over Cloud and Device


Towards Transparency in Coreference Resolution: A Quantum-Inspired Approach


Towards Transparency: Exploring LLM Trainings Datasets through Visual Topic Modeling and Semantic Frame


Towards Transparent Interactive Semantic Parsing via Step-by-Step Correction


Towards Transparent and Explainable Attention Models


Towards Transparent, Reusable, and Customizable Data Science in Computational Notebooks


Towards Trust of Explainable AI in Thyroid Nodule Diagnosis


Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors' Reasoning with Deep Reinforcement Learning


Towards Trustworthy Dataset Distillation


Towards Trustworthy Explanation: On Causal Rationalization


Towards Trustworthy GUI Agents: A Survey


Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration


Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey


Towards Ultra-High-Definition Image Deraining: A Benchmark and An Efficient Method


Towards Ultra-Low-Power Neuromorphic Speech Enhancement with Spiking-FullSubNet


Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization


Towards Ultrasound Tongue Image prediction from EEG during speech production


Towards Unbiased COVID-19 Lesion Localisation and Segmentation via Weakly Supervised Learning


Towards Unbiased Evaluation of Time-series Anomaly Detector


Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels


Towards Unbiased Visual Emotion Recognition via Causal Intervention


Towards Unbiased and Accurate Deferral to Multiple Experts


Towards Unconditional Uncloneable Encryption


Towards Understanding Adversarial Robustness of Optical Flow Networks


Towards Understanding Barriers and Mitigation Strategies of Software Engineers with Non-traditional Educational and Occupational Backgrounds


Towards Understanding Bias in Synthetic Data for Evaluation


Towards Understanding Fairness and its Composition in Ensemble Machine Learning


Towards Understanding Gender-Seniority Compound Bias in Natural Language Generation


Towards Understanding Generalization of Macro-AUC in Multi-label Learning


Towards Understanding Graphical Perception in Large Multimodal Models


Towards Understanding Grokking: An Effective Theory of Representation Learning


Towards Understanding How Data Augmentation Works with Imbalanced Data


Towards Understanding How Knowledge Evolves in Large Vision-Language Models


Towards Understanding In-Context Learning with Contrastive Demonstrations and Saliency Maps


Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis


Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation


Towards Understanding Omission in Dialogue Summarization


Towards Understanding Quality Challenges of the Federated Learning for Neural Networks: A First Look from the Lens of Robustness


Towards Understanding Sharpness-Aware Minimization


Towards Understanding Sycophancy in Language Models


Towards Understanding Third-party Library Dependency in C/C++ Ecosystem


Towards Understanding Unsafe Video Generation


Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It


Towards Understanding and Characterizing the Arbitrage Bot Scam In the Wild


Towards Understanding and Demystifying Bitcoin Mixing Services


Towards Understanding and Evaluating Structural Node Embeddings


Towards Understanding and Improving GFlowNet Training


Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation


Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning


Towards Understanding and Mitigating Social Biases in Language Models


Towards Understanding of Medical Randomized Controlled Trials by Conclusion Generation


Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms


Towards Understanding the Data Dependency of Mixup-style Training


Towards Understanding the Interplay of Generative Artificial Intelligence and the Internet


Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning


Towards Understanding the Nature of Attention with Low-Rank Sparse Decomposition


Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models


Towards Understanding the Safety Boundaries of DeepSeek Models: Evaluation and Findings


Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features


Towards Unified Benchmark and Models for Multi-Modal Perceptual Metrics


Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning


Towards Unified Keyframe Propagation Models


Towards Unified Molecule-Enhanced Pathology Image Representation Learning via Integrating Spatial Transcriptomics


Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond


Towards Unified Multimodal Editing with Enhanced Knowledge Collaboration


Towards Unified Music Emotion Recognition across Dimensional and Categorical Models


Towards Unified Robustness Against Both Backdoor and Adversarial Attacks


Towards Unified Scene Text Spotting based on Sequence Generation


Towards Unified Text-based Person Retrieval: A Large-scale Multi-Attribute and Language Search Benchmark


Towards Unified Token Learning for Vision-Language Tracking


Towards Unified and Effective Domain Generalization


Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelines


Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments


Towards Unifying Interpretability and Control: Evaluation via Intervention


Towards Unifying Medical Vision-and-Language Pre-training via Soft Prompts


Towards Unifying Reference Expression Generation and Comprehension


Towards Unifying the Label Space for Aspect- and Sentence-based Sentiment Analysis


Towards Unique and Informative Captioning of Images


Towards Universal Certified Robustness with Multi-Norm Training


Towards Universal Mesh Movement Networks


Towards Universal Neural Network Potential for Material Discovery Applicable to Arbitrary Combination of 45 Elements


Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings


Towards Universal Sequence Representation Learning for Recommender Systems


Towards Universal Texture Synthesis by Combining Texton Broadcasting with Noise Injection in StyleGAN-2


Towards Universal Unsupervised Anomaly Detection in Medical Imaging


Towards Universal and Black-Box Query-Response Only Attack on LLMs with QROA


Towards Unpolarized GPDs from Pseudo-Distributions


Towards Unsupervised Content Disentanglement in Sentence Representations via Syntactic Roles


Towards Unsupervised Deep Graph Structure Learning


Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network


Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis


Towards Unsupervised Model Selection for Domain Adaptive Object Detection


Towards Unsupervised Open World Semantic Segmentation


Towards Unsupervised Recognition of Token-level Semantic Differences in Related Documents


Towards Unsupervised Speech Recognition Without Pronunciation Models


Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models


Towards User-Driven Neural Machine Translation


Towards Using Clothes Style Transfer for Scenario-aware Person Video Generation


Towards Utilising a Range of Neural Activations for Comprehending Representational Associations


Towards V2I Age-aware Fairness Access: A DQN Based Intelligent Vehicular Node Training and Test Method


Towards Verifiability of Total Value Locked (TVL) in Decentralized Finance


Towards Verifiable Differentially-Private Polling


Towards Verifiable Generation: A Benchmark for Knowledge-aware Language Model Attribution


Towards Verified Stochastic Variational Inference for Probabilistic Programs


Towards Verifying Robustness of Neural Networks Against Semantic Perturbations


Towards Verifying the Geometric Robustness of Large-scale Neural Networks


Towards Video Anomaly Retrieval from Video Anomaly Detection: New Benchmarks and Model


Towards Vision-Language Geo-Foundation Model: A Survey


Towards Vision-Language Mechanistic Interpretability: A Causal Tracing Tool for BLIP


Towards Visual Distortion in Black-Box Attacks


Towards Visual Explanations for Convolutional Neural Networks via Input Resampling


Towards Visually Explaining Video Understanding Networks with Perturbation


Towards Vivid and Diverse Image Colorization with Generative Color Prior


Towards Voice Reconstruction from EEG during Imagined Speech


Towards Writer Retrieval for Historical Datasets


Towards Zero Touch Networks: Cross-Layer Automated Security Solutions for 6G Wireless Networks


Towards Zero and Few-shot Knowledge-seeking Turn Detection in Task-orientated Dialogue Systems


Towards Zero-Shot Coordination between Teams of Agents: The N-XPlay Framework


Towards Zero-Shot Functional Compositionality of Language Models


Towards Zero-Shot Multimodal Machine Translation


Towards Zero-resource Cross-lingual Entity Linking


Towards Zero-shot Point Cloud Anomaly Detection: A Multi-View Projection Framework


Towards a Benchmark for Causal Business Process Reasoning with LLMs


Towards a Benchmark for Fog Data Processing


Towards a Benchmark for Large Language Models for Business Process Management Tasks


Towards a Better Global Loss Landscape of GANs


Towards a Better Metric for Evaluating Question Generation Systems


Towards a Better Model with Dual Transformer for Drug Response Prediction


Towards a Better Understanding Human Reading Comprehension with Brain Signals


Towards a Better Understanding of Variations in Zero-Shot Neural Machine Translation Performance


Towards a Better Understanding of the Characteristics of Fractal Networks


Towards a Catalog of Composite Refactorings


Towards a Client-Centered Assessment of LLM Therapists by Client Simulation


Towards a Cloud-Based Ontology for Service Model Security -- Technical Report


Towards a Competitive End-to-End Speech Recognition for CHiME-6 Dinner Party Transcription


Towards a Complete Pipeline for Segmenting Nuclei in Feulgen-Stained Images


Towards a Completeness Argumentation for Scenario Concepts


Towards a Comprehensive Benchmark for Pathological Lymph Node Metastasis in Breast Cancer Sections


Towards a Comprehensive, Efficient and Promptable Anatomic Structure Segmentation Model using 3D Whole-body CT Scans


Towards a Data-Driven Requirements Engineering Approach: Automatic Analysis of User Reviews


Towards a Decomposable Metric for Explainable Evaluation of Text Generation from AMR


Towards a Deep Understanding of Multilingual End-to-End Speech Translation


Towards a Deeper Understanding of Concept Bottleneck Models Through End-to-End Explanation


Towards a Deeper Understanding of Reasoning Capabilities in Large Language Models


Towards a Defense Against Federated Backdoor Attacks Under Continuous Training


Towards a Fair Comparison and Realistic Evaluation Framework of Android Malware Detectors based on Static Analysis and Machine Learning


Towards a Formal Characterization of User Simulation Objectives in Conversational Information Access


Towards a Formal Foundation for Blockchain Rollups


Towards a Formal Foundation of Intermittent Computing


Towards a Foundation Purchasing Model: Pretrained Generative Autoregression on Transaction Sequences


Towards a Framework for Evaluating Explanations in Automated Fact Verification


Towards a GML-Enabled Knowledge Graph Platform


Towards a General Recipe for Combinatorial Optimization with Multi-Filter GNNs


Towards a General Theory of Infinite-Width Limits of Neural Classifiers


Towards a Geometric Understanding of the 4-Dimensional Point Groups


Towards a Global Search for New Physics with Isotope Shifts


Towards a Graph Neural Network-Based Approach for Estimating Hidden States in Cyber Attack Simulations


Towards a Guideline for Evaluation Metrics in Medical Image Segmentation


Towards a Holistic Framework for Multimodal Large Language Models in Three-dimensional Brain CT Report Generation


Towards a Holistic Understanding of Mathematical Questions with Contrastive Pre-training


Towards a Law of Iterated Expectations for Heuristic Estimators


Towards a Learning Theory of Cause-Effect Inference


Towards a Mechanistic Interpretation of Multi-Step Reasoning Capabilities of Language Models


Towards a Modular Architecture for Science Factories


Towards a More Generalized Approach in Open Relation Extraction


Towards a More Rigorous Science of Blindspot Discovery in Image Classification Models


Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safety


Towards a Multimodal Large Language Model with Pixel-Level Insight for Biomedicine


Towards a Path Dependent Account of Category Fluency


Towards a Perceptual Evaluation Framework for Lighting Estimation


Towards a Personal Health Knowledge Graph Framework for Patient Monitoring


Towards a Perspectivist Turn in Argument Quality Assessment


Towards a Pipeline for Real-Time Visualization of Faces for VR-based Telepresence and Live Broadcasting Utilizing Neural Rendering


Towards a Practical Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via Randomized Smoothing


Towards a Principled Integration of Multi-Camera Re-Identification and Tracking through Optimal Bayes Filters


Towards a Principled Learning Rate Adaptation for Natural Evolution Strategies


Towards a Proof System for Probabilistic Dynamic Logic


Towards a Quantum Simulation of Nonlinear Sigma Models with a Topological Term


Towards a Real-time Measure of the Perception of Anthropomorphism in Human-robot Interaction


Towards a Realistic Model for Failure Propagation in Interdependent Networks


Towards a Rigorous Evaluation of Time-series Anomaly Detection


Towards a Robust Framework for Multimodal Hate Detection: A Study on Video vs. Image-based Content


Towards a Robust Retrieval-Based Summarization System


Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms


Towards a Scalable Reference-Free Evaluation of Generative Models


Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control


Towards a Seamless Integration of Word Senses into Downstream NLP Applications


Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models


Towards a Simple Framework of Skill Transfer Learning for Robotic Ultrasound-guidance Procedures


Towards a Spatiotemporal Fusion Approach to Precipitation Nowcasting


Towards a Staging Environment for the Internet of Things


Towards a Standardized Representation for Deep Learning Collective Algorithms


Towards a Systematic Approach to Design New Ensemble Learning Algorithms


Towards a Theoretical Understanding of Synthetic Data in LLM Post-Training: A Reverse-Bottleneck Perspective


Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics


Towards a Theory of Maximal Extractable Value I: Constant Function Market Makers


Towards a Thermodynamical Deep-Learning-Vision-Based Flexible Robotic Cell for Circular Healthcare


Towards a Transformer-Based Pre-trained Model for IoT Traffic Classification


Towards a Trustworthy Anomaly Detection for Critical Applications through Approximated Partial AUC Loss


Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift


Towards a Unified Approach to Homography Estimation Using Image Features and Pixel Intensities


Towards a Unified Benchmark and Framework for Deep Learning-Based Prediction of Nuclear Magnetic Resonance Chemical Shifts


Towards a Unified Conversational Recommendation System: Multi-task Learning via Contextualized Knowledge Distillation


Towards a Unified Copernicus Foundation Model for Earth Vision


Towards a Unified Framework for Fair and Stable Graph Representation Learning


Towards a Unified Multimodal Reasoning Framework


Towards a Unified Representation Evaluation Framework Beyond Downstream Tasks


Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism


Towards a Unified View of Parameter-Efficient Transfer Learning


Towards a Unified View of Preference Learning for Large Language Models: A Survey


Towards a Unified View on Visual Parameter-Efficient Transfer Learning


Towards a Universal Gating Network for Mixtures of Experts


Towards a Value-Complemented Framework for Enabling Human Monitoring in Cyber-Physical Systems


Towards a Verified Model of the Algorand Consensus Protocol in Coq


Towards a Vision-Language Episodic Memory Framework: Large-scale Pretrained Model-Augmented Hippocampal Attractor Dynamics


Towards a Zero-One Law for Column Subset Selection


Towards a classification of entanglements of Galois representations attached to elliptic curves


Towards a classification of isolated $j$-invariants


Towards a clinically accessible radiology foundation model: open-access and lightweight, with automated evaluation


Towards a complete 3D morphable model of the human head


Towards a complete classification of 6D supergravities


Towards a comprehensive visualization of structure in data


Towards a computational definition of the tresillo rhythm and its tracing in popular music


Towards a corpus for credibility assessment in software practitioner blog articles


Towards a data-driven characterization of behavioral changes induced by the seasonal flu


Towards a fully consistent Milky Way disk model V. The disk model for 4 $-$ 14 kpc


Towards a generalization of information theory for hierarchical partitions


Towards a generalized accessibility measure for transportation equity and efficiency


Towards a geometric understanding of Spatio Temporal Graph Convolution Networks


Towards a global dynamic wind atlas: A multi-country validation of wind power simulation from MERRA-2 and ERA-5 reanalyses bias-corrected with the Global Wind Atlas


Towards a heuristic understanding of the storage effect


Towards a mathematical framework to inform Neural Network modelling via Polynomial Regression


Towards a mathematical theory of trajectory inference


Towards a more efficient computation of individual attribute and policy contribution for post-hoc explanation of cooperative multi-agent systems using Myerson values


Towards a more inductive world for drug repurposing approaches


Towards a multi-stakeholder value-based assessment framework for algorithmic systems


Towards a multi-tracer neutrino mass measurement with line-intensity mapping


Towards a multimodal framework for remote sensing image change retrieval and captioning


Towards a performance analysis on pre-trained Visual Question Answering models for autonomous driving


Towards a power analysis for PLS-based methods


Towards a robust out-of-the-box neural network model for genomic data


Towards a scalable discrete quantum generative adversarial neural network


Towards a text-based quantitative and explainable histopathology image analysis


Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size


Towards a topological-geometrical theory of group equivariant non-expansive operators for data analysis and machine learning


Towards a unified view of unsupervised non-local methods for image denoising: the NL-Ridge approach


Towards a universal QAOA protocol: Evidence of a scaling advantage in solving some combinatorial optimization problems


Towards a universal model for the density profiles of dark matter haloes


Towards accelerating physical discovery via non-interactive and interactive multi-fidelity Bayesian Optimization: Current challenges and future opportunities


Towards accurate and reliable ICU outcome prediction: a multimodal learning framework based on belief function theory using structured EHRs and free-text notes


Towards accurate instance segmentation in large-scale LiDAR point clouds


Towards aerodynamic surrogate modeling based on $β$-variational autoencoders


Towards an AI-Driven Video-Based American Sign Language Dictionary: Exploring Design and Usage Experience with Learners


Towards an Adversarially Robust Normalization Approach


Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials


Towards an Argument Mining Pipeline Transforming Texts to Argument Graphs


Towards an Automatic Analysis of CHO-K1 Suspension Growth in Microfluidic Single-cell Cultivation


Towards an Automatic Diagnosis of Peripheral and Central Palsy Using Machine Learning on Facial Features


Towards an Automatic System for Extracting Planar Orientations from Software Generated Point Clouds


Towards an Awareness of Time Series Anomaly Detection Models' Adversarial Vulnerability


Towards an Effective and Efficient Transformer for Rain-by-snow Weather Removal


Towards an Efficient ML System: Unveiling a Trade-off between Task Accuracy and Engineering Efficiency in a Large-scale Car Sharing Platform


Towards an End-to-End Framework for Invasive Brain Signal Decoding with Large Language Models


Towards an Enhanced Understanding of Bias in Pre-trained Neural Language Models: A Survey with Special Emphasis on Affective Bias


Towards an Explainable Comparison and Alignment of Feature Embeddings


Towards an Improved Metric for Evaluating Disentangled Representations


Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning


Towards an Interpretable Analysis for Estimating the Resolution Time of Software Issues


Towards an Ontology for Scenario Definition for the Assessment of Automated Vehicles: An Object-Oriented Framework


Towards an Understanding of Distributed Asymmetric Collaborative Visualization on Problem-solving


Towards an Understanding of Long-Tailed Runtimes of SLS Algorithms


Towards an Understanding of Neural Networks in Natural-Image Spaces


Towards an astronomical foundation model for stars with a Transformer-based model


Towards an objective characterization of an individual's facial movements using Self-Supervised Person-Specific-Models


Towards an open standard for assessing the severity of robot security vulnerabilities, the Robot Vulnerability Scoring System (RVSS)


Towards an open-source landscape for 3D CSEM modelling


Towards application-specific query processing systems


Towards artificial general intelligence via a multimodal foundation model


Towards automated brain aneurysm detection in TOF-MRA: open data, weak labels, and anatomical knowledge


Towards automatic initialization of registration algorithms using simulated endoscopy images


Towards benchmarking of Solidity verification tools


Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identification


Towards better traffic volume estimation: Jointly addressing the underdetermination and nonequilibrium problems with correlation-adaptive GNNs


Towards better understanding and better generalization of few-shot classification in histology images with contrastive learning


Towards better understanding of gradient-based attribution methods for Deep Neural Networks


Towards biologically plausible Dreaming and Planning in recurrent spiking networks


Towards characterising rocky worlds: Trends in chemical make-ups of M dwarfs versus GK dwarfs


Towards chemical accuracy for chemi- and physisorption with an efficient density functional


Towards chemical accuracy with shallow quantum circuits: A Clifford-based Hamiltonian engineering approach


Towards conceptual generalization in the embedding space


Towards consistency of rule-based explainer and black box model -- fusion of rule induction and XAI-based feature importance


Towards constraining warm dark matter with stellar streams through neural simulation-based inference


Towards continual task learning in artificial neural networks: current approaches and insights from neuroscience


Towards contrast-agnostic soft segmentation of the spinal cord


Towards counterfactual fairness through auxiliary variables


Towards cross-lingual distributed representations without parallel text trained with adversarial autoencoders


Towards deep generation of guided wave representations for composite materials


Towards deep learning with segregated dendrites


Towards deeper neural networks for Fast Radio Burst detection


Towards detection and classification of microscopic foraminifera using transfer learning


Towards duration robust weakly supervised sound event detection


Towards dynamic stability analysis of sustainable power grids using graph neural networks


Towards efficient representation identification in supervised learning


Towards eliciting latent knowledge from LLMs with mechanistic interpretability


Towards exascale real-time RFI mitigation


Towards explainable artificial intelligence (XAI) for early anticipation of traffic accidents


Towards explainable classifiers using the counterfactual approach -- global explanations for discovering bias in data


Towards flexible perception with visual memory


Towards frugal unsupervised detection of subtle abnormalities in medical imaging


Towards fully automated deep-learning-based brain tumor segmentation: is brain extraction still necessary?


Towards generalizable single-cell perturbation modeling via the Conditional Monge Gap


Towards generalization of drug response prediction to single cells and patients utilizing importance-aware multi-source domain transfer learning


Towards generalizing deep-audio fake detection networks


Towards generating more interpretable counterfactuals via concept vectors: a preliminary study on chest X-rays


Towards graph neural networks for provably solving convex optimization problems


Towards high photon density for Compton Scattering by spectral chirp


Towards high resolution, validated and open global wind power assessments


Towards high-accuracy deep learning inference of compressible turbulent flows over aerofoils


Towards human-compatible autonomous car: A study of non-verbal Turing test in automated driving with affective transition modelling


Towards hypergraph cognitive networks as feature-rich models of knowledge


Towards improving discriminative reconstruction via simultaneous dense and sparse coding


Towards in-store multi-person tracking using head detection and track heatmaps


Towards learning Lattice Boltzmann collision operators


Towards meta-interpretive learning of programming language semantics


Towards modular and programmable architecture search


Towards molecular docking with neutral atoms


Towards neural networks that provably know when they don't know


Towards noise contrastive estimation with soft targets for conditional models


Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging


Towards optimal nonlinearities for sparse recovery using higher-order statistics


Towards optimal sampling for learning sparse approximation in high dimensions


Towards optimal sensor placement for inverse problems in spaces of measures


Towards optimized actions in critical situations of soccer games with deep reinforcement learning


Towards order of magnitude X-ray dose reduction in breast cancer imaging using phase contrast and deep denoising


Towards out-of-distribution generalizable predictions of chemical kinetics properties


Towards overcoming data scarcity in materials science: unifying models and datasets with a mixture of experts framework


Towards pandemic preparedness: ability to estimate high-resolution social contact patterns from longitudinal surveys


Towards performant and reliable undersampled MR reconstruction via diffusion model sampling


Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving deep spatial transformers


Towards predicting Pedestrian Evacuation Time and Density from Floorplans using a Vision Transformer


Towards preserving word order importance through Forced Invalidation


Towards providing reliable job completion time predictions using PCS


Towards quantifying information flows: relative entropy in deep neural networks and the renormalization group


Towards quantitative super-resolution microscopy: Molecular maps with statistical guarantees


Towards real-time finite-strain anisotropic thermo-visco-elastodynamic analysis of soft tissues for thermal ablative therapy


Towards real-world navigation with deep differentiable planners


Towards realistic symmetry-based completion of previously unseen point clouds


Towards reliable head and neck cancers locoregional recurrence prediction using delta-radiomics and learning with rejection option


Towards replacing precipitation ensemble predictions systems using machine learning


Towards replicability with confidence intervals for the exceedance probability


Towards robust variational quantum simulation of Lindblad dynamics via stochastic Magnus expansion


Towards robust vision by multi-task learning on monkey visual cortex


Towards robust word embeddings for noisy texts


Towards safe Bayesian optimization with Wiener kernel regression


Towards scalable surrogate models based on Neural Fields for large scale aerodynamic simulations


Towards scanning nanostructure x-ray microscopy


Towards self-organized control: Using neural cellular automata to robustly control a cart-pole agent


Towards single integrated spoofing-aware speaker verification embeddings


Towards smaller, faster decoder-only transformers: Architectural variants and their implications


Towards softerware: Enabling personalization of interactive data representations for users with disabilities


Towards solar measurements of nuclear reaction rates


Towards stable training of parallel continual learning


Towards standardizing Korean Grammatical Error Correction: Datasets and Annotation


Towards synthetic generation of realistic wooden logs


Towards the $β$ function of SU(2) with adjoint matter using Pauli-Villars fields


Towards the Automated Extraction and Refactoring of NoSQL Schemas from Application Code


Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol


Towards the Characterization of Representations Learned via Capsule-based Network Architectures


Towards the D-Optimal Online Experiment Design for Recommender Selection


Towards the Detection of Diffusion Model Deepfakes


Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift


Towards the Generalization of Contrastive Self-Supervised Learning


Towards the Generation of Musical Explanations with GPT-3


Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm


Towards the Law of Capacity Gap in Distilling Language Models


Towards the Practical Utility of Federated Learning in the Medical Domain


Towards the Quantification of Safety Risks in Deep Neural Networks


Towards the Spectral bias Alleviation by Normalizations in Coordinate Networks


Towards the Uncharted: Density-Descending Feature Perturbation for Semi-supervised Semantic Segmentation


Towards the Use of Deep Reinforcement Learning with Global Policy For Query-based Extractive Summarisation


Towards the automated large-scale reconstruction of past road networks from historical maps


Towards the cellular-scale simulation of motor-driven cytoskeletal assemblies


Towards the decentralized coordination of multiple self-adaptive systems


Towards the efficacy of federated prediction for epidemics on networks


Towards the generation of synchronized and believable non-verbal facial behaviors of a talking virtual agent


Towards the real-time evolution of gauge-invariant $\mathbb{Z}_2$ and $U(1)$ quantum link models on NISQ Hardware with error-mitigation


Towards the ultimate PMT waveform analysis for neutrino and dark matter experiments


Towards tropically counting binodal surfaces


Towards true discovery of the differential equations


Towards trustworthy seizure onset detection using workflow notes


Towards unbiased recovery of cosmic filament properties: the role of spine curvature and optimized smoothing


Towards unconstrained joint hand-object reconstruction from RGB videos


Towards understanding evolution of science through language model series


Towards understanding structure-function relationships in random fiber networks


Towards universal neural nets: Gibbs machines and ACE


Towards usable automated detection of CPU architecture and endianness for arbitrary binary files and object code sequences


Towards visually prompted keyword localisation for zero-resource spoken languages


Tower: An Open Multilingual Large Language Model for Translation-Related Tasks


Tower: Data Structures in Quantum Superposition


Towers of Babel: Combining Images, Language, and 3D Geometry for Learning Multimodal Vision


Tox-BART: Leveraging Toxicity Attributes for Explanation Generation of Implicit Hate Speech


ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection


ToxiSpanSE: An Explainable Toxicity Detection in Code Review Comments


Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis


Toxic Memes: A Survey of Computational Perspectives on the Detection and Explanation of Meme Toxicities


Toxic language detection: a systematic review of Arabic datasets


ToxicTone: A Mandarin Audio Dataset Annotated for Toxicity and Toxic Utterance Tonality


Toxicity Detection in Drug Candidates using Simplified Molecular-Input Line-Entry System


Toxicity Detection: Does Context Really Matter?


Toxicity of the Commons: Curating Open-Source Pre-Training Data


ToyADMOS: A Dataset of Miniature-Machine Operating Sounds for Anomalous Sound Detection


ToyArchitecture: Unsupervised Learning of Interpretable Models of the World


TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs


TrADe Re-ID -- Live Person Re-Identification using Tracking and Anomaly Detection


TrAISformer -- A Transformer Network with Sparse Augmented Data Representation and Cross Entropy Loss for AIS-based Vessel Trajectory Prediction


TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional Regression


TrOMR:Transformer-Based Polyphonic Optical Music Recognition


Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning


TraCE: Trajectory Counterfactual Explanation Scores


TraCS: Trajectory Collection in Continuous Space under Local Differential Privacy


TraClets: Harnessing the power of computer vision for trajectory classification


TraCon: A novel dataset for real-time traffic cones detection using deep learning


TraDE: Network and Traffic-aware Adaptive Scheduling for Microservices Under Dynamics


TraDiffusion: Trajectory-Based Training-Free Image Generation


TraF-Align: Trajectory-aware Feature Alignment for Asynchronous Multi-agent Perception


TraM : Enhancing User Sleep Prediction with Transformer-based Multivariate Time Series Modeling and Machine Learning Ensembles


TraM-NeRF: Tracing Mirror and Near-Perfect Specular Reflections through Neural Radiance Fields


TraNCE: Transformative Non-linear Concept Explainer for CNNs


TraND: Transferable Neighborhood Discovery for Unsupervised Cross-domain Gait Recognition


TraSCE: Trajectory Steering for Concept Erasure


TraVLR: Now You See It, Now You Don't! A Bimodal Dataset for Evaluating Visio-Linguistic Reasoning


TraVaS: Differentially Private Trace Variant Selection for Process Mining


Trabant: A Serverless Architecture for Multi-Tenant Orbital Edge Computing


TracLLM: A Generic Framework for Attributing Long Context LLMs


Trace Diagnostics for Signal-based Temporal Properties


Trace Norm Regularised Deep Multi-Task Learning


Trace Typing: An Approach for Evaluating Retrofitted Type Systems (Extended Version)


Trace formulation for photonic inverse design with incoherent sources


Trace norm regularization for multi-task learning with scarce data


Trace your sources in large-scale data: one ring to find them all


Trace-Relating Compiler Correctness and Secure Compilation


Trace-class Gaussian priors for Bayesian learning of neural networks with MCMC


TraceDiff: Debugging Unexpected Code Behavior Using Trace Divergences


TraceMesh: Scalable and Streaming Sampling for Distributed Traces


TraceNet: Tracing and Locating the Key Elements in Sentiment Analysis


Traceability Transformed: Generating moreAccurate Links with Pre-Trained BERT Models


Traceable Automatic Feature Transformation via Cascading Actor-Critic Agents


Traceable Group-Wise Self-Optimizing Feature Transformation Learning: A Dual Optimization Perspective


Traceable LLM-based validation of statements in knowledge graphs


TraceableSpeech: Towards Proactively Traceable Text-to-Speech with Watermarking


Traces of Memorisation in Large Language Models for Code


Tracing Antisemitic Language Through Diachronic Embedding Projections: France 1789-1914


Tracing Back Music Emotion Predictions to Sound Sources and Intuitive Perceptual Qualities


Tracing Forum Posts to MOOC Content using Topic Analysis


Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network


Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion Recognition


Tracing Network Evolution Using the PARAFAC2 Model


Tracing Origins: Coreference-aware Machine Reading Comprehension


Tracing Transactions Across Cryptocurrency Ledgers


Tracing Vulnerabilities in Maven: A Study of CVE lifecycles and Dependency Networks


Tracing and Manipulating Intermediate Values in Neural Math Problem Solvers


Tracing cultural diachronic semantic shifts in Russian using word embeddings: test sets and baselines


Tracing prices: A flow-based cost allocation for optimized power systems


Tracing the Development of the Virtual Particle Concept Using Semantic Change Detection


Tracing the Roots of Facts in Multilingual Language Models: Independent, Shared, and Transferred Knowledge


Tracing the evolution of short-period binaries with super-synchronous fast rotators


Tracing the large-scale magnetic field morphology in protoplanetary disks using molecular line polarization


Tracing the origins of SARS-CoV-2 in coronavirus phylogenies


Track Anything Annotate: Video annotation and dataset generation of computer vision models


Track Anything: Segment Anything Meets Videos


Track the Answer: Extending TextVQA from Image to Video with Spatio-Temporal Clues


Track to Reconstruct and Reconstruct to Track


Track without Appearance: Learn Box and Tracklet Embedding with Local and Global Motion Patterns for Vehicle Tracking


Track-On: Transformer-based Online Point Tracking with Memory


Track2Vec: fairness music recommendation with a GPU-free customizable-driven framework


TrackFormers: In Search of Transformer-Based Particle Tracking for the High-Luminosity LHC Era


TrackMe:A Simple and Effective Multiple Object Tracking Annotation Tool


TrackNet: A Triplet metric-based method for Multi-Target Multi-Camera Vehicle Tracking


TrackOcc: Camera-based 4D Panoptic Occupancy Tracking


TrackPGD: Efficient Adversarial Attack using Object Binary Masks against Robust Transformer Trackers


TrackSSM: A General Motion Predictor by State-Space Model


Trackastra: Transformer-based cell tracking for live-cell microscopy


Tracker Installations Are Not Created Equal: Understanding Tracker Configuration of Form Data Collection


Tracker Meets Night: A Transformer Enhancer for UAV Tracking


Tracking Algorithms for TPCs using Consensus-Based Robust Estimators


Tracking Anything with Decoupled Video Segmentation


Tracking Blobs in the Turbulent Edge Plasma of a Tokamak Fusion Device


Tracking Brand-Associated Polarity-Bearing Topics in User Reviews


Tracking Changing Probabilities via Dynamic Learners


Tracking Discourse Influence in Darknet Forums


Tracking Emotions: Intrinsic Motivation Grounded on Multi-Level Prediction Error Dynamics


Tracking Everything Everywhere All at Once


Tracking Fringe and Coordinated Activity on Twitter Leading Up To the US Capitol Attack


Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras


Tracking Holistic Object Representations


Tracking Interaction States for Multi-Turn Text-to-SQL Semantic Parsing


Tracking Knowledge Propagation Across Wikipedia Languages


Tracking Meets Large Multimodal Models for Driving Scenario Understanding


Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance


Tracking Network Dynamics using Probabilistic State-Space Models


Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version)


Tracking Objects as Pixel-wise Distributions


Tracking Partially-Occluded Deformable Objects while Enforcing Geometric Constraints


Tracking Persons-of-Interest via Unsupervised Representation Adaptation


Tracking Temporal Evolution of Graphs using Non-Timestamped Data


Tracking Transforming Objects: A Benchmark


Tracking Where Events Take Place: Reverse Spatial Term Queries on Streaming Data


Tracking active nests in solar-type pulsators: Ensemble starspot modelling of Kepler asteroseismic targets


Tracking all members of a honey bee colony over their lifetime


Tracking and Following a Suspended Moving Object using Camera-Based Vision System


Tracking and forecasting oscillatory data streams using Koopman autoencoders and Kalman filtering


Tracking and triangulating firefly flashes in field recordings


Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers


Tracking by Joint Local and Global Search: A Target-aware Attention based Approach


Tracking by weakly-supervised learning and graph optimization for whole-embryo C. elegans lineages


Tracking environmental policy changes in the Brazilian Federal Official Gazette


Tracking fast and slow changes in synaptic weights from simultaneously observed pre- and postsynaptic spiking


Tracking perovskite crystallization via deep learning-based feature detection on 2D X-ray scattering data


Tracking solar radio bursts using Bayesian multilateration


Tracking the 2024 US Presidential Election Chatter on Tiktok: A Public Multimodal Dataset


Tracking the Diffusion of Named Entities


Tracking the Electron Density Changes in Excited States -- A Computational Study on Pyrazine


Tracking the Flight: Exploring a Computational Framework for Analyzing Escape Responses in Plains Zebra (Equus quagga)


Tracking the Takes and Trajectories of English-Language News Narratives across Trustworthy and Worrisome Websites


Tracking the Transmission Dynamics of COVID-19 with a Time-Varying Coefficient State-Space Model


Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods


Tracking the topology of neural manifolds across populations


Tracking the validity of the quasi-static and sub-horizon approximations in modified gravity


Tracking through Containers and Occluders in the Wild


Tracking-Assisted Object Detection with Event Cameras


Tracking-by-Trackers with a Distilled and Reinforced Model


Trackintel: An open-source Python library for human mobility analysis


Tracks to Modernity: Railroads, Growth, and Social Movements in Denmark


TracrBench: Generating Interpretability Testbeds with Large Language Models


TractOracle: towards an anatomically-informed reward function for RL-based tractography


TractShapeNet: Efficient Multi-Shape Learning with 3D Tractography Point Clouds


Tractable Approach to MmWaves Cellular Analysis with FSO Backhauling under Feedback Delay and Hardware Limitations


Tractable Bayesian Density Regression via Logit Stick-Breaking Priors


Tractable Bounding of Counterfactual Queries by Knowledge Compilation


Tractable Computation of Expected Kernels


Tractable Control for Autoregressive Language Generation


Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems


Tractable Evaluation of Stein's Unbiased Risk Estimate with Convex Regularizers


Tractable Function-Space Variational Inference in Bayesian Neural Networks


Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks


Tractable Ridge Regression for Paired Comparisons


Tractable Uncertainty for Structure Learning


Tractable higher-order under-approximating AE extensions for non-linear systems


Traction Control Allocation Employing Vehicle Motion Feedback Controller for Four-wheel-independent-drive Vehicle


Tractor beams with optimal pulling force using structured waves


Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading


Trade-Offs Between Fairness and Privacy in Language Modeling


Trade-off between deep learning for species identification and inference about predator-prey co-occurrence: Reproducible R workflow integrating models in computer vision and ecological statistics


Trade-off between predictive performance and FDR control for high-dimensional Gaussian model selection


Trade-off between reconstruction loss and feature alignment for domain generalization


Trade-off between validity and efficiency of merging p-values under arbitrary dependence


Trade-offs between sustainable development goals in systems of cities


Trade-offs in Fine-tuned Diffusion Models Between Accuracy and Interpretability


Trade-offs in Large Reasoning Models: An Empirical Analysis of Deliberative and Adaptive Reasoning over Foundational Capabilities


Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning


Trade-offs in Privacy-Preserving Eye Tracking through Iris Obfuscation: A Benchmarking Study


Tradeoffs Between Alignment and Helpfulness in Language Models with Representation Engineering


Trading Information between Latents in Hierarchical Variational Autoencoders


Trading Positional Complexity vs. Deepness in Coordinate Networks


Trading off regional and overall energy system design flexibility in the net-zero transition


Trading oxygen for iron I: the [O/Fe] -- specific star formation rate relation of galaxies


Trading with Time Series Causal Discovery: An Empirical Study


TradingAgents: Multi-Agents LLM Financial Trading Framework


Traditional Chinese Synthetic Datasets Verified with Labeled Data for Scene Text Recognition


Traditional Method Inspired Deep Neural Network for Edge Detection


TrafFormer: A Transformer Model for Predicting Long-term Traffic


Traffic Centralization and Digital Sovereignty: An Analysis Under the Lens of DNS Servers


Traffic Control Gesture Recognition for Autonomous Vehicles


Traffic Equations for Fluid Networks with Overflows


Traffic Flow Data Completion and Anomaly Diagnosis via Sparse and Low-Rank Tensor Optimization


Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network


Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding


Traffic Forecasting on New Roads Using Spatial Contrastive Pre-Training (SCPT)


Traffic Forecasting on Traffic Moving Snippets


Traffic Forecasting using Vehicle-to-Vehicle Communication


Traffic Incident Database with Multiple Labels Including Various Perspective Environmental Information


Traffic Light Control with Reinforcement Learning


Traffic Matrix Estimation based on Denoising Diffusion Probabilistic Model


Traffic Prediction Framework for OpenStreetMap using Deep Learning based Complex Event Processing and Open Traffic Cameras


Traffic Scenario Clustering by Iterative Optimisation of Self-Supervised Networks Using a Random Forest Activation Pattern Similarity


Traffic Scenario Logic: A Spatial-Temporal Logic for Modeling and Reasoning of Urban Traffic Scenarios


Traffic Scene Parsing through the TSP6K Dataset


Traffic Sign Recognition Dataset and Data Augmentation


Traffic Signal Control Using Lightweight Transformers: An Offline-to-Online RL Approach


Traffic Signal Cycle Control with Centralized Critic and Decentralized Actors under Varying Intervention Frequencies


Traffic Simulator for Multibeam Satellite Communication Systems


Traffic State Estimation from Vehicle Trajectories with Anisotropic Gaussian Processes


Traffic Weaver: semi-synthetic time-varying traffic generator based on averaged time series


Traffic estimation in unobserved network locations using data-driven macroscopic models


Traffic expertise meets residual RL: Knowledge-informed model-based residual reinforcement learning for CAV trajectory control


Traffic flow prediction using Deep Sedenion Networks


Traffic incident duration prediction via a deep learning framework for text description encoding


Traffic map prediction using UNet based deep convolutional neural network


Traffic signal optimization in large-scale urban road networks: an adaptive-predictive controller using Ising models


Traffic4cast -- Large-scale Traffic Prediction using 3DResNet and Sparse-UNet


Traffic4cast-Traffic Map Movie Forecasting -- Team MIE-Lab


TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction


TrafficFlowGAN: Physics-informed Flow based Generative Adversarial Network for Uncertainty Quantification


TrafficGPT: Viewing, Processing and Interacting with Traffic Foundation Models


TrafficGamer: Reliable and Flexible Traffic Simulation for Safety-Critical Scenarios with Game-Theoretic Oracles


TrafficKAN-GCN: Graph Convolutional-based Kolmogorov-Arnold Network for Traffic Flow Optimization


TrafficLLM: Enhancing Large Language Models for Network Traffic Analysis with Generic Traffic Representation


TrafficSafetyGPT: Tuning a Pre-trained Large Language Model to a Domain-Specific Expert in Transportation Safety


TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning


TrafficVLM: A Controllable Visual Language Model for Traffic Video Captioning


Tragedy Plus Time: Capturing Unintended Human Activities from Weakly-labeled Videos


TraianProt: a user-friendly R shiny application for wide format proteomics data downstream analysis


Train Ego-Path Detection on Railway Tracks Using End-to-End Deep Learning


Train More Parameters But Mind Their Placement: Insights into Language Adaptation with PEFT


Train No Evil: Selective Masking for Task-Guided Pre-Training


Train Offline, Test Online: A Real Robot Learning Benchmark


Train Once, Deploy Anywhere: Matryoshka Representation Learning for Multimodal Recommendation


Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning


Train Once, Use Flexibly: A Modular Framework for Multi-Aspect Neural News Recommendation


Train Scheduling with Hybrid Answer Set Programming


Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models


Train Till You Drop: Towards Stable and Robust Source-free Unsupervised 3D Domain Adaptation


Train Your Data Processor: Distribution-Aware and Error-Compensation Coordinate Decoding for Human Pose Estimation


Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs


Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity


Train longer, generalize better: closing the generalization gap in large batch training of neural networks


Train on classical, deploy on quantum: scaling generative quantum machine learning to a thousand qubits


Train, Sort, Explain: Learning to Diagnose Translation Models


Train-Attention: Meta-Learning Where to Focus in Continual Knowledge Learning


Train-Free Segmentation in MRI with Cubical Persistent Homology


Trainability, Expressivity and Interpretability in Gated Neural ODEs


Trainable Discrete Feature Embeddings for Variational Quantum Classifier


Trainable Highly-expressive Activation Functions


Trainable Joint Channel Estimation, Detection and Decoding for MIMO URLLC Systems


Trainable Loss Weights in Super-Resolution


Trainable Projected Gradient Method for Robust Fine-tuning


Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion


Trainable Weight Averaging: A General Approach for Subspace Training


Trainable and Explainable Simplicial Map Neural Networks


Trainable back-propagated functional transfer matrices


Trained MT Metrics Learn to Cope with Machine-translated References


Trained Model in Supervised Deep Learning is a Conditional Risk Minimizer


Trained Models Tell Us How to Make Them Robust to Spurious Correlation without Group Annotation


Trained Random Forests Completely Reveal your Dataset


Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context


Trained on 100 million words and still in shape: BERT meets British National Corpus


Training Adversarial Agents to Exploit Weaknesses in Deep Control Policies


Training Artificial Neural Networks by Generalized Likelihood Ratio Method: Exploring Brain-like Learning to Improve Robustness


Training Audio Captioning Models without Audio


Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction


Training Bayesian Neural Networks with Sparse Subspace Variational Inference


Training Big Random Forests with Little Resources


Training Binary Neural Networks with Real-to-Binary Convolutions


Training CNN Classifiers for Semantic Segmentation using Partially Annotated Images: with Application on Human Thigh and Calf MRI


Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds


Training Class-Imbalanced Diffusion Model Via Overlap Optimization


Training Classifiers that are Universally Robust to All Label Noise Levels


Training Classifiers with Natural Language Explanations


Training Compact CNNs for Image Classification using Dynamic-coded Filter Fusion


Training Compute-Optimal Protein Language Models


Training Consistency Models with Variational Noise Coupling


Training Convolutional Neural Networks With Hebbian Principal Component Analysis


Training Cross-Lingual embeddings for Setswana and Sepedi


Training Cross-Morphology Embodied AI Agents: From Practical Challenges to Theoretical Foundations


Training Data Attribution for Diffusion Models


Training Data Augmentation for Dysarthric Automatic Speech Recognition by Text-to-Dysarthric-Speech Synthesis


Training Data Influence Analysis and Estimation: A Survey


Training Data Provenance Verification: Did Your Model Use Synthetic Data from My Generative Model for Training?


Training Data Subset Selection for Regression with Controlled Generalization Error


Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data


Training Deep 3D Convolutional Neural Networks to Extract BSM Physics Parameters Directly from HEP Data: a Proof-of-Concept Study Using Monte Carlo Simulations


Training Deep Capsule Networks with Residual Connections


Training Deep Energy-Based Models with f-Divergence Minimization


Training Deep Networks from Zero to Hero: avoiding pitfalls and going beyond


Training Deep Neural Networks via Branch-and-Bound


Training Deep Neural Networks via Direct Loss Minimization


Training Domain Specific Models for Energy-Efficient Object Detection


Training Domain-invariant Object Detector Faster with Feature Replay and Slow Learner


Training Dynamics of Contextual N-Grams in Language Models


Training Efficient CNNS: Tweaking the Nuts and Bolts of Neural Networks for Lighter, Faster and Robust Models


Training Efficient Controllers via Analytic Policy Gradient


Training Energy-Based Normalizing Flow with Score-Matching Objectives


Training Ensembles to Detect Adversarial Examples


Training Ensembles with Inliers and Outliers for Semi-supervised Active Learning


Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach


Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State


Training Feedforward Neural Networks with Bayesian Hyper-Heuristics


Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra


Training Free Graph Neural Networks for Graph Matching


Training Frozen Feature Pyramid DINOv2 for Eyelid Measurements with Infinite Encoding and Orthogonal Regularization


Training GANs with Stronger Augmentations via Contrastive Discriminator


Training Generative Adversarial Networks Via Turing Test


Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators


Training Generative Adversarial Networks in One Stage


Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation


Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts


Training Generative Networks with general Optimal Transport distances


Training Graph Neural Networks with 1000 Layers


Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization


Training Guarantees of Neural Network Classification Two-Sample Tests by Kernel Analysis


Training Heterogeneous Features in Sequence to Sequence Tasks: Latent Enhanced Multi-filter Seq2Seq Model


Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation


Training Implicit Generative Models via an Invariant Statistical Loss


Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters


Training Invertible Neural Networks as Autoencoders


Training LLM-based Tutors to Improve Student Learning Outcomes in Dialogues


Training LLMs to Recognize Hedges in Spontaneous Narratives


Training Language Models Using Target-Propagation


Training Language Models for Social Deduction with Multi-Agent Reinforcement Learning


Training Language Models on Synthetic Edit Sequences Improves Code Synthesis


Training Language Models to Generate Text with Citations via Fine-grained Rewards


Training Language Models to Reason Efficiently


Training Language Models to Win Debates with Self-Play Improves Judge Accuracy


Training Language Models with Language Feedback at Scale


Training Language Models with Memory Augmentation


Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning


Training Large-Scale Optical Neural Networks with Two-Pass Forward Propagation


Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation


Training Long-Context LLMs Efficiently via Chunk-wise Optimization


Training Matting Models without Alpha Labels


Training Multi-bit Quantized and Binarized Networks with A Learnable Symmetric Quantizer


Training Natural Language Processing Models on Encrypted Text for Enhanced Privacy


Training Naturalized Semantic Parsers with Very Little Data


Training Networks in Null Space of Feature Covariance for Continual Learning


Training Neural Machine Translation To Apply Terminology Constraints


Training Neural Networks for and by Interpolation


Training Neural Networks on Data Sources with Unknown Reliability


Training Neural Networks with Fixed Sparse Masks


Training Neural Networks with Local Error Signals


Training Neural Samplers with Reverse Diffusive KL Divergence


Training Normalizing Flows from Dependent Data


Training OOD Detectors in their Natural Habitats


Training Provably Robust Models by Polyhedral Envelope Regularization


Training Quantum Embedding Kernels on Near-Term Quantum Computers


Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning


Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis


Training Robust Graph Neural Networks by Modeling Noise Dependencies


Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes


Training Set Reconstruction from Differentially Private Forests: How Effective is DP?


Training Simplification and Model Simplification for Deep Learning: A Minimal Effort Back Propagation Method


Training Socially Aligned Language Models on Simulated Social Interactions


Training Software Engineering Agents and Verifiers with SWE-Gym


Training Sparse Neural Networks using Compressed Sensing


Training Spiking Deep Networks for Neuromorphic Hardware


Training Spiking Neural Networks with Local Tandem Learning


Training Step-Level Reasoning Verifiers with Formal Verification Tools


Training Strategies for Deep Learning Gravitational-Wave Searches


Training Stronger Baselines for Learning to Optimize


Training Structured Mechanical Models by Minimizing Discrete Euler-Lagrange Residual


Training Structured Neural Networks Through Manifold Identification and Variance Reduction


Training Subset Selection for Weak Supervision


Training Temporal Word Embeddings with a Compass


Training Thinner and Deeper Neural Networks: Jumpstart Regularization


Training Trajectories of Language Models Across Scales


Training Transformer Models by Wavelet Losses Improves Quantitative and Visual Performance in Single Image Super-Resolution


Training Transformers with 4-bit Integers


Training Transition Policies via Distribution Matching for Complex Tasks


Training Turn-by-Turn Verifiers for Dialogue Tutoring Agents: The Curious Case of LLMs as Your Coding Tutors


Training Unbiased Diffusion Models From Biased Dataset


Training Uncertainty-Aware Classifiers with Conformalized Deep Learning


Training Verifiers to Solve Math Word Problems


Training Vision-Language Models with Less Bimodal Supervision


Training Your Sparse Neural Network Better with Any Mask


Training a Fully Convolutional Neural Network to Route Integrated Circuits


Training a General Spiking Neural Network with Improved Efficiency and Minimum Latency


Training a Label-Noise-Resistant GNN with Reduced Complexity


Training a Neural Network for Gibbs and Noise Removal in Diffusion MRI


Training a Resilient Q-Network against Observational Interference


Training a Subsampling Mechanism in Expectation


Training a Two Layer ReLU Network Analytically


Training a neural netwok for data reduction and better generalization


Training an Assassin AI for The Resistance: Avalon


Training an Ising Machine with Equilibrium Propagation


Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors


Training and Evaluating Language Models with Template-based Data Generation


Training and Evaluating a Jupyter Notebook Data Science Assistant


Training and Evaluating with Human Label Variation: An Empirical Study


Training and Generating Neural Networks in Compressed Weight Space


Training and Inference on Any-Order Autoregressive Models the Right Way


Training and Predicting Visual Error for Real-Time Applications


Training and Tuning Generative Neural Radiance Fields for Attribute-Conditional 3D-Aware Face Generation


Training atomic neural networks using fragment-based data generated in virtual reality


Training biases in machine learning for the analytic continuation of quantum many-body Green's functions


Training compact deep learning models for video classification using circulant matrices


Training convolutional neural networks with cheap convolutions and online distillation


Training deep neural networks with low precision multiplications


Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability


Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time


Training individually fair ML models with Sensitive Subspace Robustness


Training language models to follow instructions with human feedback


Training neural nets to learn reactive potential energy surfaces using interactive quantum chemistry in virtual reality


Training neural networks using Metropolis Monte Carlo and an adaptive variant


Training neural networks without backpropagation using particles


Training neural operators to preserve invariant measures of chaotic attractors


Training normalizing flows with computationally intensive target probability distributions


Training objective drives the consistency of representational similarity across datasets


Training of deep residual networks with stochastic MG/OPT


Training on Thin Air: Improve Image Classification with Generated Data


Training on test proteins improves fitness, structure, and function prediction


Training on the Benchmark Is Not All You Need


Training on the Test Model: Contamination in Ranking Distillation


Training on the Test Task Confounds Evaluation and Emergence


Training privacy-preserving video analytics pipelines by suppressing features that reveal information about private attributes


Training quantum machine learning models on cloud without uploading the data


Training robust and generalizable quantum models


Training robust neural networks using Lipschitz bounds


Training speaker recognition systems with limited data


Training toward significance with the decorrelated event classifier transformer neural network


Training with More Confidence: Mitigating Injected and Natural Backdoors During Training


Training β-VAE by Aggregating a Learned Gaussian Posterior with a Decoupled Decoder


Training-Free Acceleration of ViTs with Delayed Spatial Merging


Training-Free Activation Sparsity in Large Language Models


Training-Free Condition Video Diffusion Models for single frame Spatial-Semantic Echocardiogram Synthesis


Training-Free Dataset Pruning for Instance Segmentation


Training-Free Efficient Video Generation via Dynamic Token Carving


Training-Free Exponential Context Extension via Cascading KV Cache


Training-Free Hierarchical Scene Understanding for Gaussian Splatting with Superpoint Graphs


Training-Free Layout Control with Cross-Attention Guidance


Training-Free Multi-Step Audio Source Separation


Training-Free Neural Active Learning with Initialization-Robustness Guarantees


Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis


Training-Free Text-Guided Image Editing with Visual Autoregressive Model


Training-Free Unsupervised Prompt for Vision-Language Models


Training-Free Voice Conversion with Factorized Optimal Transport


Training-Free Watermarking for Autoregressive Image Generation


Training-Set Distillation for Real-Time UAV Object Tracking


Training-and-Prompt-Free General Painterly Harmonization via Zero-Shot Disentenglement on Style and Content References


Training-free Boost for Open-Vocabulary Object Detection with Confidence Aggregation


Training-free Composite Scene Generation for Layout-to-Image Synthesis


Training-free Diffusion Model Alignment with Sampling Demons


Training-free Graph Neural Networks and the Power of Labels as Features


Training-free Heterogeneous Graph Condensation via Data Selection


Training-free Heterogeneous Model Merging


Training-free LLM Merging for Multi-task Learning


Training-free Lexical Backdoor Attacks on Language Models


Training-free Neural Architecture Search for RNNs and Transformers


Training-free Neural Architecture Search through Variance of Knowledge of Deep Network Weights


Training-free Object Counting with Prompts


Training-free Regional Prompting for Diffusion Transformers


Training-free Ultra Small Model for Universal Sparse Reconstruction in Compressed Sensing


Training-free Video Temporal Grounding using Large-scale Pre-trained Models


Training-free Zero-shot Composed Image Retrieval via Weighted Modality Fusion and Similarity


Trainwreck: A damaging adversarial attack on image classifiers


TraitLab: a Matlab package for fitting and simulating binary tree-like data


TrajAgent: An Agent Framework for Unified Trajectory Modelling


TrajCogn: Leveraging LLMs for Cognizing Movement Patterns and Travel Purposes from Trajectories


TrajDeleter: Enabling Trajectory Forgetting in Offline Reinforcement Learning Agents


TrajDiffuse: A Conditional Diffusion Model for Environment-Aware Trajectory Prediction


TrajEvo: Designing Trajectory Prediction Heuristics via LLM-driven Evolution


TrajFlow: A Generative Framework for Occupancy Density Estimation Using Normalizing Flows


TrajGAIL: Generating Urban Vehicle Trajectories using Generative Adversarial Imitation Learning


TrajGPT: Controlled Synthetic Trajectory Generation Using a Multitask Transformer-Based Spatiotemporal Model


TrajLLM: A Modular LLM-Enhanced Agent-Based Framework for Realistic Human Trajectory Simulation


TrajLearn: Trajectory Prediction Learning using Deep Generative Models


TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models


TrajPRed: Trajectory Prediction with Region-based Relation Learning


TrajPy: empowering feature engineering for trajectory analysis across domains


TrajSceneLLM: A Multimodal Perspective on Semantic GPS Trajectory Analysis


Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data


Trajectory Clustering Performance Evaluation: If we know the answer, it's not clustering


Trajectory Encoding Temporal Graph Networks


Trajectory Extending Kinetic Monte Carlo Simulations to Evaluate Pure and Gas Mixture Diffusivities through a Dense Polymeric Membrane


Trajectory Flow Matching with Applications to Clinical Time Series Modeling


Trajectory Forecasting on Temporal Graphs


Trajectory Forecasting through Low-Rank Adaptation of Discrete Latent Codes


Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans


Trajectory Generation, Control, and Safety with Denoising Diffusion Probabilistic Models


Trajectory Inference via Mean-field Langevin in Path Space


Trajectory Inference with Smooth Schrödinger Bridges


Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies


Trajectory Optimisation of a Swarm Orbiting 67P/Churyumov-Gerasimenko Maximising Gravitational Signal


Trajectory Optimization Under Stochastic Dynamics Leveraging Maximum Mean Discrepancy


Trajectory Optimization for Adaptive Informative Path Planning with Multimodal Sensing


Trajectory Optimization with Optimization-Based Dynamics


Trajectory Planning Under Environmental Uncertainty With Finite-Sample Safety Guarantees


Trajectory Prediction & Path Planning for an Object Intercepting UAV with a Mounted Depth Camera


Trajectory Prediction Meets Large Language Models: A Survey


Trajectory Prediction for Autonomous Driving with Topometric Map


Trajectory Prediction with Graph-based Dual-scale Context Fusion


Trajectory Prediction with Latent Belief Energy-Based Model


Trajectory Space Factorization for Deep Video-Based 3D Human Pose Estimation


Trajectory Test-Train Overlap in Next-Location Prediction Datasets


Trajectory Tracking via Multiscale Continuous Attractor Networks


Trajectory World Models for Heterogeneous Environments


Trajectory inference for a branching SDE model of cell differentiation


Trajectory of Alternating Direction Method of Multipliers and Adaptive Acceleration


Trajectory-Aware Body Interaction Transformer for Multi-Person Pose Forecasting


Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning


Trajectory-Aware Rate Adaptation for Flying Networks


Trajectory-Based Individualized Treatment Rules


Trajectory-User Linking via Hierarchical Spatio-Temporal Attention Networks


Trajectory-based Road Autolabeling with Lidar-Camera Fusion in Winter Conditions


Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline


Trajectory-guided Motion Perception for Facial Expression Quality Assessment in Neurological Disorders


Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning


TrajectoryFormer: 3D Object Tracking Transformer with Predictive Trajectory Hypotheses


TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics


Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data


Trakhtenbrot's Theorem in Coq: Finite Model Theory through the Constructive Lens


Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization


TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data


TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning with Structure-Trajectory Prompted Reconstruction for Person Re-Identification


TranSHER: Translating Knowledge Graph Embedding with Hyper-Ellipsoidal Restriction


TranSMS: Transformers for Super-Resolution Calibration in Magnetic Particle Imaging


TranSalNet: Towards perceptually relevant visual saliency prediction


TranSplat: Surface Embedding-guided 3D Gaussian Splatting for Transparent Object Manipulation


Tranco: A Research-Oriented Top Sites Ranking Hardened Against Manipulation


Trans-Dimensional Bayesian Inference for Gravitational Lens Substructures


Trans-Dimensional Generative Modeling via Jump Diffusion Models


Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations


Trans-Tokenization and Cross-lingual Vocabulary Transfers: Language Adaptation of LLMs for Low-Resource NLP


Trans-Zero: Self-Play Incentivizes Large Language Models for Multilingual Translation Without Parallel Data


Trans2k: Unlocking the Power of Deep Models for Transparent Object Tracking


Trans4D: Realistic Geometry-Aware Transition for Compositional Text-to-4D Synthesis


Trans4Map: Revisiting Holistic Bird's-Eye-View Mapping from Egocentric Images to Allocentric Semantics with Vision Transformers


TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest


TransAction: ICL-SJTU Submission to EPIC-Kitchens Action Anticipation Challenge 2021


TransAdapter: Vision Transformer for Feature-Centric Unsupervised Domain Adaptation


TransAgent: Transfer Vision-Language Foundation Models with Heterogeneous Agent Collaboration


TransAttUnet: Multi-level Attention-guided U-Net with Transformer for Medical Image Segmentation


TransBench: Breaking Barriers for Transferable Graphical User Interface Agents in Dynamic Digital Environments


TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion


TransBoost: Improving the Best ImageNet Performance using Deep Transduction


TransCAB: Transferable Clean-Annotation Backdoor to Object Detection with Natural Trigger in Real-World


TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation


TransCDR: a deep learning model for enhancing the generalizability of cancer drug response prediction through transfer learning and multimodal data fusion for drug representation


TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and a Grasping Baseline


TransCL: Transformer Makes Strong and Flexible Compressive Learning


TransCORALNet: A Two-Stream Transformer CORAL Networks for Supply Chain Credit Assessment Cold Start


TransCT: Dual-path Transformer for Low Dose Computed Tomography


TransCoder: Towards Unified Transferable Code Representation Learning Inspired by Human Skills


TransCrowd: weakly-supervised crowd counting with transformers


TransDARC: Transformer-based Driver Activity Recognition with Latent Space Feature Calibration


TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation


TransDocAnalyser: A Framework for Offline Semi-structured Handwritten Document Analysis in the Legal Domain


TransDocs: Optical Character Recognition with word to word translation


TransDreamerV3: Implanting Transformer In DreamerV3


TransESC: Smoothing Emotional Support Conversation via Turn-Level State Transition


TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphs


TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing


TransFA: Transformer-based Representation for Face Attribute Evaluation


TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation


TransFace: Calibrating Transformer Training for Face Recognition from a Data-Centric Perspective


TransFool: An Adversarial Attack against Neural Machine Translation Models


TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation


TransFusion -- A Transparency-Based Diffusion Model for Anomaly Detection


TransFusion: A Practical and Effective Transformer-based Diffusion Model for 3D Human Motion Prediction


TransFusion: Cross-view Fusion with Transformer for 3D Human Pose Estimation


TransFusion: Generating Long, High Fidelity Time Series using Diffusion Models with Transformers


TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers


TransFusion: Transcribing Speech with Multinomial Diffusion


TransFusionOdom: Interpretable Transformer-based LiDAR-Inertial Fusion Odometry Estimation


TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems


TransGOP: Transformer-Based Gaze Object Prediction


TransGrasp: Grasp Pose Estimation of a Category of Objects by Transferring Grasps from Only One Labeled Instance


TransHP: Image Classification with Hierarchical Prompting


TransICD: Transformer Based Code-wise Attention Model for Explainable ICD Coding


TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear Subspaces


TransLIST: A Transformer-Based Linguistically Informed Sanskrit Tokenizer


TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields


TransMA: an explainable multi-modal deep learning model for predicting properties of ionizable lipid nanoparticles in mRNA delivery


TransMI: A Framework to Create Strong Baselines from Multilingual Pretrained Language Models for Transliterated Data


TransMLA: Multi-Head Latent Attention Is All You Need


TransMRSR: Transformer-based Self-Distilled Generative Prior for Brain MRI Super-Resolution


TransMUSIC: A Transformer-Aided Subspace Method for DOA Estimation with Low-Resolution ADCs


TransMask: A Compact and Fast Speech Separation Model Based on Transformer


TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification


TransMix: Attend to Mix for Vision Transformers


TransMorph: Transformer for unsupervised medical image registration


TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly Detection


TransNeXt: Robust Foveal Visual Perception for Vision Transformers


TransNet: A deep network for fast detection of common shot transitions


TransNorm: Transformer Provides a Strong Spatial Normalization Mechanism for a Deep Segmentation Model


TransNuSeg: A Lightweight Multi-Task Transformer for Nuclei Segmentation


TransOMCS: From Linguistic Graphs to Commonsense Knowledge


TransONet: Automatic Segmentation of Vasculature in Computed Tomographic Angiograms Using Deep Learning


TransPL: VQ-Code Transition Matrices for Pseudo-Labeling of Time Series Unsupervised Domain Adaptation


TransPath: Learning Heuristics For Grid-Based Pathfinding via Transformers


TransPeakNet: Solvent-Aware 2D NMR Prediction via Multi-Task Pre-Training and Unsupervised Learning


TransPixeler: Advancing Text-to-Video Generation with Transparency


TransPlace: Transferable Circuit Global Placement via Graph Neural Network


TransPolymer: a Transformer-based language model for polymer property predictions


TransPose: Keypoint Localization via Transformer


TransPose: Real-time 3D Human Translation and Pose Estimation with Six Inertial Sensors


TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection


TransRUPNet for Improved Polyp Segmentation


TransRadar: Adaptive-Directional Transformer for Real-Time Multi-View Radar Semantic Segmentation


TransRank: Self-supervised Video Representation Learning via Ranking-based Transformation Recognition


TransReID: Transformer-based Object Re-Identification


TransResNet: Integrating the Strengths of ViTs and CNNs for High Resolution Medical Image Segmentation via Feature Grafting


TransResU-Net: Transformer based ResU-Net for Real-Time Colonoscopy Polyp Segmentation


TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data


TransSleep: Transitioning-aware Attention-based Deep Neural Network for Sleep Staging


TransTIC: Transferring Transformer-based Image Compression from Human Perception to Machine Perception


TransTab: Learning Transferable Tabular Transformers Across Tables


TransTrack: Multiple Object Tracking with Transformer


TransURL: Improving malicious URL detection with multi-layer Transformer encoding and multi-scale pyramid features


TransVCL: Attention-enhanced Video Copy Localization Network with Flexible Supervision


TransVFC: A Transformable Video Feature Compression Framework for Machines


TransVIP: Speech to Speech Translation System with Voice and Isochrony Preservation


TransVOS: Video Object Segmentation with Transformers


TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions


TransWorldNG: Traffic Simulation via Foundation Model


TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition


TransY-Net:Learning Fully Transformer Networks for Change Detection of Remote Sensing Images


TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning


TransZero: Attribute-guided Transformer for Zero-Shot Learning


Transaction Fees on a Honeymoon: Ethereum's EIP-1559 One Month Later


Transaction Proximity: A Graph-Based Approach to Blockchain Fraud Prevention


Transactions on Red-black and AVL trees in NVRAM


Transcendental Idealism of Planner: Evaluating Perception from Planning Perspective for Autonomous Driving


Transcending Adversarial Perturbations: Manifold-Aided Adversarial Examples with Legitimate Semantics


Transcending Fusion: A Multi-Scale Alignment Method for Remote Sensing Image-Text Retrieval


Transcending the Attention Paradigm: Representation Learning from Geospatial Social Media Data


Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary


Transcoded Video Restoration by Temporal Spatial Auxiliary Network


Transcoders Find Interpretable LLM Feature Circuits


Transcranial ultrasound simulation with uncertainty estimation


Transcription free filler word detection with Neural semi-CRFs


Transcriptome signature for the identification of bevacizumab responders in ovarian cancer


Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression based convolutional neural networks


Transcriptomics-based matching of drugs to diseases with deep learning


Transcriptomics-guided Slide Representation Learning in Computational Pathology


Transcripts per million ratio: applying distribution-aware normalisation over the popular TPM method


Transdimensional inference for gravitational-wave astronomy with Bilby


Transducer Tuning: Efficient Model Adaptation for Software Tasks Using Code Property Graphs


Transductive Few-Shot Classification on the Oblique Manifold


Transductive Few-Shot Learning: Clustering is All You Need?


Transductive Few-shot Learning with Prototype-based Label Propagation by Iterative Graph Refinement


Transductive Learning for Unsupervised Text Style Transfer


Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification


Transductive Visual Verb Sense Disambiguation


Transductive Zero-Shot Hashing for Multilabel Image Retrieval


Transductive Zero-Shot Learning with Visual Structure Constraint


Transductive conformal inference with adaptive scores


Transductively Informed Inductive Program Synthesis


TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems


Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings


Transfer CLIP for Generalizable Image Denoising


Transfer Entropy Rate Through Lempel-Ziv Complexity


Transfer Entropy in Graph Convolutional Neural Networks


Transfer Knowledge from Head to Tail: Uncertainty Calibration under Long-tailed Distribution


Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation


Transfer Learning Assisted Fast Design Migration Over Technology Nodes: A Study on Transformer Matching Network


Transfer Learning Based Multi-Objective Genetic Algorithm for Dynamic Community Detection


Transfer Learning Between Different Architectures Via Weights Injection


Transfer Learning Between Related Tasks Using Expected Label Proportions


Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations


Transfer Learning Enhanced Generative Adversarial Networks for Multi-Channel MRI Reconstruction


Transfer Learning Facilitates the Prediction of Polymer-Surface Adhesion Strength


Transfer Learning Robustness in Multi-Class Categorization by Fine-Tuning Pre-Trained Contextualized Language Models


Transfer Learning and Bias Correction with Pre-trained Audio Embeddings


Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on African Languages


Transfer Learning between Motor Imagery Datasets using Deep Learning -- Validation of Framework and Comparison of Datasets


Transfer Learning for Activity Recognition in Mobile Health


Transfer Learning for Cross-dataset Isolated Sign Language Recognition in Under-Resourced Datasets


Transfer Learning for Deep Learning-based Prediction of Lattice Thermal Conductivity


Transfer Learning for Electricity Price Forecasting


Transfer Learning for HVAC System Fault Detection


Transfer Learning for Image-Based Malware Classification


Transfer Learning for Improving Model Predictions in Highly Configurable Software


Transfer Learning for Improving Results on Russian Sentiment Datasets


Transfer Learning for Improving Singing-voice Detection in Polyphonic Instrumental Music


Transfer Learning for Low-Resource Sentiment Analysis


Transfer Learning for Microstructure Segmentation with CS-UNet: A Hybrid Algorithm with Transformer and CNN Encoders


Transfer Learning for Mining Feature Requests and Bug Reports from Tweets and App Store Reviews


Transfer Learning for Molecular Property Predictions from Small Data Sets


Transfer Learning for Node Regression Applied to Spreading Prediction


Transfer Learning for Non-Intrusive Load Monitoring


Transfer Learning for Nonparametric Contextual Dynamic Pricing


Transfer Learning for OCRopus Model Training on Early Printed Books


Transfer Learning for Performance Modeling of Configurable Systems: A Causal Analysis


Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis


Transfer Learning for Pose Estimation of Illustrated Characters


Transfer Learning for Protein Structure Classification at Low Resolution


Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation Study


Transfer Learning for Sequence Generation: from Single-source to Multi-source


Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks


Transfer Learning for Speech Recognition on a Budget


Transfer Learning for T-Cell Response Prediction


Transfer Learning for Temporal Link Prediction


Transfer Learning for the Efficient Detection of COVID-19 from Smartphone Audio Data


Transfer Learning from Monolingual ASR to Transcription-free Cross-lingual Voice Conversion


Transfer Learning from Synthetic to Real-Noise Denoising with Adaptive Instance Normalization


Transfer Learning from Visual Speech Recognition to Mouthing Recognition in German Sign Language


Transfer Learning in ECG Diagnosis: Is It Effective?


Transfer Learning in Information Criteria-based Feature Selection


Transfer Learning in Large-scale Gaussian Graphical Models with False Discovery Rate Control


Transfer Learning in Latent Contextual Bandits with Covariate Shift Through Causal Transportability


Transfer Learning of CATE with Kernel Ridge Regression


Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures


Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization


Transfer Learning of RSSI to Improve Indoor Localisation Performance


Transfer Learning of an Ensemble of DNNs for SSVEP BCI Spellers without User-Specific Training


Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation


Transfer Learning using Spectral Convolutional Autoencoders on Semi-Regular Surface Meshes


Transfer Learning via Unsupervised Task Discovery for Visual Question Answering


Transfer Learning with Deep Tabular Models


Transfer Learning with Gaussian Processes for Bayesian Optimization


Transfer Learning with Joint Fine-Tuning for Multimodal Sentiment Analysis


Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows


Transfer Learning with Pretrained Remote Sensing Transformers


Transfer Learning with Pseudo Multi-Label Birdcall Classification for DS@GT BirdCLEF 2024


Transfer Learning with Reconstruction Loss


Transfer Learning with Self-Supervised Vision Transformers for Snake Identification


Transfer Learning with Semi-Supervised Dataset Annotation for Birdcall Classification


Transfer Learning with Synthetic Corpora for Spatial Role Labeling and Reasoning


Transfer Learning-based Channel Estimation in Orthogonal Frequency Division Multiplexing Systems Using Data-nulling Superimposed Pilots


Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations


Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction


Transfer and Alignment Network for Generalized Category Discovery


Transfer and Multi-Task Learning for Noun-Noun Compound Interpretation


Transfer learning approach to Classify the X-ray image that corresponds to corona disease Using ResNet50 pretrained by ChexNet


Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network


Transfer learning for atomistic simulations using GNNs and kernel mean embeddings


Transfer learning for conflict and duplicate detection in software requirement pairs


Transfer learning for day-ahead load forecasting: a case study on European national electricity demand time series


Transfer learning for galaxy feature detection: Finding Giant Star-forming Clumps in low redshift galaxies using Faster R-CNN


Transfer learning for piecewise-constant mean estimation: Optimality, $\ell_1$- and $\ell_0$-penalisation


Transfer learning for time series classification


Transfer learning for time series classification using synthetic data generation


Transfer learning from a sparsely annotated dataset of 3D medical images


Transfer learning in genome-wide association studies with knockoffs


Transfer learning method in the problem of binary classification of chest X-rays


Transfer learning on large datasets for the accurate prediction of material properties


Transfer learning with affine model transformation


Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls