{"total":68,"rows":[{"id":"2505.24867","title":"Time Blindness: Why Video-Language Models Can't See What Humans Can?","created":"2025-05-30","cited_by_count":18,"area":"mllm"},{"id":"2504.13122","title":"VistaDPO: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models","created":"2025-04-17","cited_by_count":17,"area":"alignment"},{"id":"2509.11866","title":"Dr.V: A Hierarchical Perception-Temporal-Cognition Framework to Diagnose Video Hallucination by Fine-grained Spatial-Temporal Grounding","created":"2025-09-15","cited_by_count":13,"area":null},{"id":"2508.03100","title":"AVATAR: Reinforcement Learning to See, Hear, and Reason Over Video","created":"2025-08-05","cited_by_count":12,"area":"lr"},{"id":"2508.21496","title":"ELV-Halluc: Benchmarking Semantic Aggregation Hallucinations in Long Video Understanding","created":"2025-08-29","cited_by_count":10,"area":"mllm"},{"id":"2512.04643","title":"SEASON: Mitigating Temporal Hallucination in Video Large Language Models via Self-Diagnostic Contrastive Decoding","created":"2025-12-04","cited_by_count":10,"area":null},{"id":"2512.18671","title":"SmartSight: Mitigating Hallucination in Video-LLMs Without Compromising Video Understanding via Temporal Attention Collapse","created":"2025-12-21","cited_by_count":9,"area":null},{"id":"2505.12826","title":"Mitigating Hallucination in VideoLLMs via Temporal-Aware Activation Engineering","created":"2025-05-19","cited_by_count":8,"area":"mllm"},{"id":"2510.05034","title":"Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models","created":"2025-10-06","cited_by_count":8,"area":"lr"},{"id":"2504.12083","title":"Self-alignment of Large Video Language Models with Refined Regularized Preference Optimization","created":"2025-04-16","cited_by_count":7,"area":"alignment"},{"id":"2510.03584","title":"FrameOracle: Learning What to See and How Much to See in Videos","created":"2025-10-04","cited_by_count":7,"area":"mllm"},{"id":"2601.04073","title":"Analyzing Reasoning Consistency in Large Multimodal Models under Cross-Modal Conflicts","created":"2026-01-07","cited_by_count":7,"area":"lr"},{"id":"2512.05513","title":"Know-Show: Benchmarking Video-Language Models on Spatio-Temporal Grounded Reasoning","created":"2025-12-05","cited_by_count":5,"area":"lr"},{"id":"2512.11215","title":"SmokeBench: Evaluating Multimodal Large Language Models for Wildfire Smoke Detection","created":"2025-12-12","cited_by_count":5,"area":"mllm"},{"id":"2602.17555","title":"GraphThinker: Reinforcing Temporally Grounded Video Reasoning with Event Graph Thinking","created":"2026-02-19","cited_by_count":5,"area":"lr"},{"id":"2601.04778","title":"CounterVid: Counterfactual Video Generation for Mitigating Action and Temporal Hallucinations in Video-Language Models","created":"2026-01-08","cited_by_count":4,"area":null},{"id":"2604.12424","title":"Decoding by Perturbation: Mitigating MLLM Hallucinations via Dynamic Textual Perturbation","created":"2026-04-14","cited_by_count":3,"area":"mllm"},{"id":"2508.10955","title":"Empowering Multimodal LLMs with External Tools: A Comprehensive Survey","created":"2025-08-14","cited_by_count":2,"area":"mllm"},{"id":"2508.18859","title":"Harnessing Meta-Learning for Controllable Full-Frame Video Stabilization","created":"2025-08-26","cited_by_count":2,"area":null},{"id":"2509.08538","title":"MESH -- Understanding Videos Like Human: Measuring Hallucinations in Large Video Models","created":"2025-09-10","cited_by_count":2,"area":null},{"id":"2511.06475","title":"NOAH: Benchmarking Narrative Prior driven Hallucination and Omission in Video Large Language Models","created":"2025-11-09","cited_by_count":2,"area":null},{"id":"2603.07071","title":"VirtueBench: Evaluating Trustworthiness under Uncertainty in Long Video Understanding","created":"2026-03-07","cited_by_count":2,"area":"mllm"},{"id":"2604.01460","title":"Reinforcing Consistency in Video MLLMs with Structured Rewards","created":"2026-04-01","cited_by_count":2,"area":"mllm"},{"id":"2605.16385","title":"Hilbert-Geo: Solving Solid Geometric Problems by Neural-Symbolic Reasoning","created":"2026-05-11","cited_by_count":2,"area":"lr"},{"id":"2606.31933","title":"No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs","created":"2026-06-30","cited_by_count":2,"area":null},{"id":"2507.06523","title":"FIFA: Unified Faithfulness Evaluation Framework for Text-to-Video and Video-to-Text Generation","created":"2025-07-09","cited_by_count":1,"area":"mllm"},{"id":"2509.20278","title":"Quantifying LLM Biases Across Instruction Boundary in Mixed Question Forms","created":"2025-09-24","cited_by_count":1,"area":null},{"id":"2510.13315","title":"Self-Aug: Query and Entropy Adaptive Decoding for Large Vision-Language Models","created":"2025-10-15","cited_by_count":1,"area":"mllm"},{"id":"2601.22574","title":"Enhancing Video Representations with Spatiotemporal-Semantic Residual to Mitigate Hallucinations in Video Large Multimodal Models","created":"2026-01-30","cited_by_count":1,"area":"mllm"},{"id":"2602.00559","title":"Learning to Decode Against Compositional Hallucination in Video Multimodal Large Language Models","created":"2026-01-31","cited_by_count":1,"area":"mllm"},{"id":"2602.01390","title":"Toward Scalable Audio Description Quality Control: A Workflow for Evaluating Human and VLM Raters","created":"2026-02-01","cited_by_count":1,"area":null},{"id":"2602.10639","title":"VideoSTF: Stress-Testing Output Repetition in Video Large Language Models","created":"2026-02-11","cited_by_count":1,"area":null},{"id":"2602.11244","title":"Stress Tests REVEAL Fragile Temporal and Visual Grounding in Video-Language Models","created":"2026-02-11","cited_by_count":1,"area":null},{"id":"2604.03045","title":"STEAR: Layer-Aware Spatiotemporal Evidence Intervention for Hallucination Mitigation in Video Large Language Models","created":"2026-04-03","cited_by_count":1,"area":null},{"id":"2604.12944","title":"Distorted or Fabricated? A Survey on Hallucination in Video LLMs","created":"2026-04-14","cited_by_count":1,"area":null},{"id":"2604.17873","title":"Spatiotemporal Sycophancy: Negation-Based Gaslighting in Video Large Language Models","created":"2026-04-20","cited_by_count":1,"area":null},{"id":"2604.20460","title":"CCTVBench: Contrastive Consistency Traffic VideoQA Benchmark for Multimodal LLMs","created":"2026-04-22","cited_by_count":1,"area":"mllm"},{"id":"2604.22226","title":"Towards Temporal Compositional Reasoning in Long-Form Sports Videos","created":"2026-04-24","cited_by_count":1,"area":"lr"},{"id":"2605.19075","title":"CRAFT: Critic-Refined Adaptive Key-Frame Targeting for Multimodal Video Question Answering","created":"2026-05-18","cited_by_count":1,"area":null},{"id":"2605.21988","title":"Learning Spatiotemporal Sensitivity in Video LLMs via Counterfactual Reinforcement Learning","created":"2026-05-21","cited_by_count":1,"area":null},{"id":"2607.01117","title":"MoHallBench: A Benchmark for Motion Hallucination in Video Large Language Models","created":"2026-07-01","cited_by_count":1,"area":null},{"id":"2608.03160","title":"Caved or Convinced: Temporal Sampling Gates Claim Deference in Video Large Language Models","created":"2026-08-04","cited_by_count":1,"area":null},{"id":"2501.10483","title":"ArxEval: Evaluating Retrieval and Generation in Language Models for Scientific Literature","created":"2025-01-17","cited_by_count":0,"area":null},{"id":"2511.18463","title":"Decoupling Perception from Reasoning for Hallucination-Resistant Video Understanding","created":"2025-11-23","cited_by_count":0,"area":"lr"},{"id":"2601.10010","title":"VERHallu: Evaluating and Mitigating Event Relation Hallucination in Video Large Language Models","created":"2026-01-15","cited_by_count":0,"area":null},{"id":"2603.05184","title":"Logi-PAR: Logic-Infused Patient Activity Recognition via Differentiable Rule","created":"2026-03-05","cited_by_count":0,"area":null},{"id":"2603.15260","title":"AGCD: Agent-Guided Cross-Modal Decoding for Weather Forecasting","created":"2026-03-16","cited_by_count":0,"area":"agents"},{"id":"2603.23934","title":"Revealing Multi-View Hallucination in Large Vision-Language Models","created":"2026-03-25","cited_by_count":0,"area":"mllm"},{"id":"2604.12582","title":"Relaxing Anchor-Frame Dominance for Mitigating Hallucinations in Video Large Language Models","created":"2026-04-14","cited_by_count":0,"area":null},{"id":"2604.13313","title":"Concrete Jungle: Towards Concreteness Paved Contrastive Negative Mining for Compositional Understanding","created":"2026-04-14","cited_by_count":0,"area":"mllm"},{"id":"2604.17375","title":"When Text Hijacks Vision: Benchmarking and Mitigating Text Overlay-Induced Hallucination in Vision Language Models","created":"2026-04-19","cited_by_count":0,"area":"mllm"},{"id":"2605.05348","title":"How Do Novice Describers Edit AI Drafts? The Role of Draft Quality in Audio Description Authoring","created":"2026-05-06","cited_by_count":0,"area":null},{"id":"2605.08974","title":"Tracking the Truth: Object-Centric Spatio-Temporal Monitoring for Video Large Language Models","created":"2026-05-09","cited_by_count":0,"area":"mllm"},{"id":"2605.09904","title":"TOC-Bench: A Temporal Object Consistency Benchmark for Video Large Language Models","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2605.27101","title":"Pop-Up Distractions Reveal Bag-of-Events Behavior in Video Large Language Models","created":"2026-05-26","cited_by_count":0,"area":null},{"id":"2606.11792","title":"MultiToP: Learning to Patch Visual Tokens to Mitigate Hallucinations in Video Large Multimodal Models","created":"2026-06-10","cited_by_count":0,"area":"mllm"},{"id":"2606.23061","title":"MotionHalluc: Diagnosing Kinematic Hallucinations in Fine-Grained Motion Reasoning","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2608.23474","title":"What's the Catch? Evaluating Temporal Consistency in Vision-Language Models","created":"2026-08-24","cited_by_count":0,"area":"mllm"},{"id":"2609.09895","title":"Can We Trust Video Hallucination Detectors? VidHalLoc for Evaluating the Evaluators","created":"2026-09-09","cited_by_count":0,"area":null},{"id":"2609.13288","title":"Target-Checked Reliability Score Refinement for Video Question Answering","created":"2026-09-09","cited_by_count":0,"area":null},{"id":"2609.24452","title":"Do LiDAR Language Models Really Understand Spatio-temporal Relationships?","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2609.27327","title":"Can Vision-Language Models Analyze Human-Centered Video? Mapping Model Capabilities and Human-AI Collaborative Workflows","created":"2026-09-23","cited_by_count":0,"area":"mllm"},{"id":"2609.28991","title":"Beneath the Scores: Rethinking Hallucination Evaluation for Video Understanding Models","created":"2026-09-24","cited_by_count":0,"area":"lr"},{"id":"2609.29607","title":"STRAND: Benchmarking and Improving Object-Centric Spatio-Temporal Monitoring in Video Large Language Models","created":"2026-08-28","cited_by_count":0,"area":"mllm"},{"id":"2610.01595","title":"Before It Fades: Reinforcing Temporal Representations at Inference Time in VideoLLMs","created":"2026-10-01","cited_by_count":0,"area":"lr"},{"id":"2610.02976","title":"Relevant Evidence Decoding for Audio-Visual Hallucination Mitigation","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.03400","title":"Beyond Entropy: Self-Diagnostic Multi-Role Token Optimization for Video Reasoning","created":"2026-10-02","cited_by_count":0,"area":"lr"},{"id":"2610.19728","title":"Mitigating Video Hallucinations via Attention-Guided Representation Perturbation","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}