Computer Science3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations →3D U-Net: Learning Dense Volumetric Segmentation From Sparse Annotation →3D Vision-Language Gaussian Splatting →A Comprehensive Overview of Large Language Models (LLMs) for Cyber Defences: Opportunities and Directions →A Comprehensive Survey on Kolmogorov Arnold Networks (KAN) →A Novel Paradigm Boosting Translation Capabilities of Large Language Models →A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends →A Survey on Hardware Accelerators for Large Language Models →A Survey on Kolmogorov-Arnold Network →A Survey on Text-to-3D Contents Generation in the Wild →A Tale of Tails: Model Collapse as a Change of Scaling Laws →AgentClinic: A Multimodal Agent Benchmark to Evaluate AI in Simulated Clinical Environments →AgentReview: Exploring Peer Review Dynamics With LLM Agents →AI and Personalized Learning: Bridging the Gap With Modern Educational Goals →Applications of Deep Neural Networks With Keras →Audio Anti-Spoofing Detection: A Survey →AutoLoRA: Automatically Tuning Matrix Ranks in Low-Rank Adaptation Based on Meta Learning →Automating Research Synthesis With Domain-Specific Large Language Model Fine-Tuning →BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks on Large Language Models →BASS: Batched Attention-Optimized Speculative Sampling →Benchmarking Vision Language Models for Cultural Understanding →Beyond the Imitation Game: Quantifying and Extrapolating the Capabilities of Language Models →Can LLMs Separate Instructions From Data? and What Do We Even Mean by That? →CFPL-FAS: Class Free Prompt Learning for Generalizable Face Anti-Spoofing →COCONut: Modernizing COCO Segmentation →CodeAid: Evaluating a Classroom Deployment of an LLM-Based Programming Assistant That Balances Student and Educator Needs →COIG-CQIA: Quality Is All You Need for Chinese Instruction Fine-Tuning →Compression Represents Intelligence Linearly →Consistency Guided Knowledge Retrieval and Denoising in LLMs for Zero-Shot Document-Level Relation Triplet Extraction →Correlation-Decoupled Knowledge Distillation for Multimodal Sentiment Analysis With Incomplete Modalities →CRAG – Comprehensive RAG Benchmark →Croissant: A Metadata Format for ML-Ready Datasets →Curriculum Reinforcement Learning for Quantum Architecture Search Under Hardware Errors →Datasheet for the Pile →Decentralized Multi-Robot Navigation for Autonomous Surface Vehicles With Distributional Reinforcement Learning →DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning →Defending Large Language Models Against Jailbreak Attacks via Layer-Specific Editing →Dense Reward for Free in Reinforcement Learning From Human Feedback →Depth-Aware Test-Time Training for Zero-Shot Video Object Segmentation →DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation →Diffusion Models, Image Super-Resolution and Everything: A Survey →DiLightNet: Fine-Grained Lighting Control for Diffusion-Based Image Generation →Do Language Models Plan Ahead for Future Tokens? →Do Membership Inference Attacks Work on Large Language Models? →DriVLMe: Enhancing LLM-Based Autonomous Driving Agents With Embodied and Social Experiences →Dual Operating Modes of In-Context Learning →Dynamic Prompt Optimizing for Text-to-Image Generation →EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage →Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Models →Enhancing Large Language Models for Text-to-Testcase Generation →Entropy Is Not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors →Ethical and Social Risks of Harm From Language Models →Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation →Exploring the Potential of Large Language Models in Self-Adaptive Systems →Flow Matching Imitation Learning for Multi-Support Manipulation →FusionMamba: Dynamic Feature Enhancement for Multimodal Image Fusion With Mamba →Gemini: A Family of Highly Capable Multimodal Models →Generative Pretrained Hierarchical Transformer for Time Series Forecasting →Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages →Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models →How Reliable Is Your Simulator? Analysis on the Limitations of Current LLM-Based User Simulators for Conversational Recommendation →How to Use and Interpret Activation Patching →HyperFast: Instant Classification for Tabular Data →InFusion: Inpainting 3D Gaussians via Learning Depth Completion From Diffusion Prior →Intelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generation →InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning →Is Vanilla MLP in Neural Radiance Field Enough for Few-Shot View Synthesis? →JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models →KAN 2.0: Kolmogorov-Arnold Networks Meet Science →Kolmogorov-Arnold Networks Are Radial Basis Function Networks →Language Models for Code Completion: A Practical Evaluation →Language Ranker: A Metric for Quantifying LLM Performance Across High and Low-Resource Languages →Large Language Model With Graph Convolution for Recommendation →LatentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction →Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation →LLARVA: Vision-Action Instruction Tuning Enhances Robot Learning →LLM-SR: Scientific Equation Discovery via Programming With Large Language Models →Low-Rank Few-Shot Adaptation of Vision-Language Models →M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detection →MagicTime: Time-Lapse Video Generation Models as Metamorphic Simulators →MDPO: Conditional Preference Optimization for Multimodal Large Language Models →Merge, Ensemble, and Cooperate! a Survey on Collaborative Strategies in the Era of Large Language Models →Meta-Prompting for Automating Zero-Shot Visual Recognition With LLMs →Meta-Rewarding Language Models: Self-Improving Alignment With LLM-as-a-Meta-Judge →MileBench: Benchmarking MLLMs in Long Context →MOMENT: A Family of Open Time-Series Foundation Models →MuAViC: A Multilingual Audio-Visual Corpus for Robust Speech Recognition and Robust Speech-to-Text Translation →Multi-Object Hallucination in Vision-Language Models →Multi-Perspective Improvement of Knowledge Graph Completion With Large Language Models →Multimodal Prompt Learning With Missing Modalities for Sentiment Analysis and Emotion Recognition →NuNER: Entity Recognition Encoder Pre-Training via LLM-Annotated Data →On the Properties of Neural Machine Translation: Encoder-Decoder Approaches →OPEN TEACH: A Versatile Teleoperation System for Robotic Manipulation →Open X-Embodiment: Robotic Learning Datasets and RT-X Models →Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-Regressive Visual Generation →OpenDataLab: Empowering General Artificial Intelligence With Open Datasets →OpenTab: Advancing Large Language Models as Open-Domain Table Reasoners →Paint by Inpaint: Learning to Add Image Objects by Removing Them First →Personalized Language Modeling From Personalized Human Feedback →Personalized Wireless Federated Learning for Large Language Models →PlanAgent: A Multi-Modal Large Language Agent for Closed-Loop Vehicle Motion Planning →Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs →Probing the Creativity of Large Language Models: Can Models Produce Divergent Semantic Association? →Raidar: GeneRative AI Detection via Rewriting →Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives →Reinforcement Learning for Collision-Free Flight Exploiting Deep Collision Encoding →Research on Autonomous Robots Navigation Based on Reinforcement Learning →RT-DETRv2: Improved Baseline With Bag-of-Freebies for Real-Time Detection Transformer →Self-Discover: Large Language Models Self-Compose Reasoning Structures →SemScore: Automated Evaluation of Instruction-Tuned LLMs Based on Semantic Textual Similarity →Singing Voice Data Scaling-Up: An Introduction to ACE-Opencpop and ACE-KiSing →SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models →Slow and Steady Wins the Race: Maintaining Plasticity With Hare and Tortoise Networks →Spectral Networks and Locally Connected Networks on Graphs →Spiral of Silence: How Is Large Language Model Killing Information Retrieval? – A Case Study on Open Domain Question Answering →STAG4D: Spatial-Temporal Anchored Generative 4D Gaussians →Synthetic Data (Almost) From Scratch: Generalized Instruction Tuning for Language Models →T3: Transparent Tracking Triggering for Fine-Grained Overlap of Compute Collectives →The Interspeech 2024 Challenge on Speech Processing Using Discrete Units →The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models →The Unreasonable Effectiveness of Eccentric Automatic Prompts →Thinking Tokens for Language Modeling →To Generate or to Retrieve? on the Effectiveness of Artificial Contexts for Medical Open-Domain Question Answering →Top Leaderboard Ranking = Top Coding Proficiency, Always? EvoEval: Evolving Coding Benchmarks via LLM →Towards Explainable, Safe Autonomous Driving With Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis With Real-World Data Sets →Towards Interpretable Hate Speech Detection Using Large Language Model-Extracted Rationales →TRAM: Global Trajectory and Motion of 3D Humans From In-the-Wild Videos →Transcriptomics-Guided Slide Representation Learning in Computational Pathology →Transformers, Parallel Computation, and Logarithmic Depth →Typos That Broke the RAG's Back: Genetic Attack on RAG Pipeline by Simulating Documents in the Wild via Low-Level Perturbations →Uncertainty Quantification on Clinical Trial Outcome Prediction →Understanding Deep Learning Requires Rethinking Generalization →Understanding Robustness of Visual State Space Models for Image Classification →Understanding Test-Time Augmentation →UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler →UniGarmentManip: A Unified Framework for Category-Level Garment Manipulation via Dense Visual Correspondence →Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation →VCR-Graphormer: A Mini-Batch Graph Transformer via Virtual Connections →Versatile Behavior Diffusion for Generalized Traffic Agent Simulation →Visibility Into AI Agents →What if We Recaption Billions of Web Images With LLaMA-3? →WildGaussians: 3D Gaussian Splatting in the Wild →WPO: Enhancing RLHF With Weighted Preference Optimization →ZipCache: Accurate and Efficient KV Cache Quantization With Salient Token Identification →