{"total":73,"rows":[{"id":"2503.01773","title":"Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areas","created":"2025-03-03","cited_by_count":95,"area":"lr"},{"id":"2401.10529","title":"Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences","created":"2024-01-19","cited_by_count":94,"area":"lr"},{"id":"2404.16635","title":"TinyChart: Efficient Chart Understanding with Visual Token Merging and Program-of-Thoughts Learning","created":"2024-04-25","cited_by_count":52,"area":"lr"},{"id":"2410.15926","title":"Mitigating Object Hallucination via Concentric Causal Attention","created":"2024-10-21","cited_by_count":49,"area":"lr"},{"id":"2405.15683","title":"Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs","created":"2024-05-24","cited_by_count":33,"area":"lr"},{"id":"2509.25848","title":"More Thought, Less Accuracy? On the Dual Nature of Reasoning in Vision-Language Models","created":"2025-09-30","cited_by_count":27,"area":"lr"},{"id":"2408.17150","title":"Look, Compare, Decide: Alleviating Hallucination in Large Vision-Language Models via Multi-View Multi-Path Reasoning","created":"2024-08-30","cited_by_count":23,"area":"lr"},{"id":"2412.03704","title":"Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension","created":"2024-12-04","cited_by_count":23,"area":"lr"},{"id":"2502.01969","title":"Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration","created":"2025-02-04","cited_by_count":23,"area":"lr"},{"id":"2504.00640","title":"POPEN: Preference-Based Optimization and Ensemble for LVLM-Based Reasoning Segmentation","created":"2025-04-01","cited_by_count":22,"area":"lr"},{"id":"2412.13949","title":"Cracking the Code of Hallucination in LVLMs with Vision-aware Head Divergence","created":"2024-12-18","cited_by_count":19,"area":"lr"},{"id":"2501.09997","title":"Attention-guided Self-reflection for Zero-shot Hallucination Detection in Large Language Models","created":"2025-01-17","cited_by_count":16,"area":"lr"},{"id":"2502.12359","title":"LanP: Rethinking the Impact of Language Priors in Large Vision-Language Models","created":"2025-02-17","cited_by_count":14,"area":"lr"},{"id":"2510.21323","title":"VL-SAE: Interpreting and Enhancing Vision-Language Alignment with a Unified Concept Set","created":"2025-10-24","cited_by_count":13,"area":"lr"},{"id":"2603.13366","title":"Thinking in Uncertainty: Mitigating Hallucinations in MLRMs with Latent Entropy-Aware Decoding","created":"2026-03-09","cited_by_count":12,"area":"lr"},{"id":"2503.18623","title":"Training-Free Personalization via Retrieval and Reasoning on Fingerprints","created":"2025-03-24","cited_by_count":10,"area":"lr"},{"id":"2509.25177","title":"Mitigating Hallucination in Multimodal LLMs with Layer Contrastive Decoding","created":"2025-09-29","cited_by_count":10,"area":"lr"},{"id":"2505.24872","title":"ProxyThinker: Test-Time Guidance through Small Visual Reasoners","created":"2025-05-30","cited_by_count":8,"area":"lr"},{"id":"2508.02419","title":"Modality Bias in LVLMs: Analyzing and Mitigating Object Hallucination via Attention Lens","created":"2025-08-04","cited_by_count":8,"area":"lr"},{"id":"2410.23114","title":"Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Models","created":"2024-10-30","cited_by_count":7,"area":"lr"},{"id":"2602.23306","title":"ThinkOmni: Lifting Textual Reasoning to Omni-modal Scenarios via Guidance Decoding","created":"2026-02-26","cited_by_count":7,"area":"lr"},{"id":"2604.01840","title":"Not All Tokens See Equally: Perception-Grounded Policy Optimization for Large Vision-Language Models","created":"2026-04-02","cited_by_count":7,"area":"lr"},{"id":"2605.13156","title":"Dual-Pathway Circuits of Object Hallucination in Vision-Language Models","created":"2026-05-13","cited_by_count":7,"area":"lr"},{"id":"2603.14337","title":"On the Nature of Attention Sink that Shapes Decoding Strategy in Omni-LLMs","created":"2026-03-15","cited_by_count":6,"area":"lr"},{"id":"2504.08809","title":"Decoupling Contrastive Decoding: Robust Hallucination Mitigation in Multimodal Large Language Models","created":"2025-04-09","cited_by_count":5,"area":"lr"},{"id":"2509.15361","title":"Beyond Spurious Signals: Debiasing Multimodal Large Language Models via Counterfactual Inference and Adaptive Expert Routing","created":"2025-09-18","cited_by_count":5,"area":"lr"},{"id":"2502.12591","title":"CutPaste&Find: Efficient Multimodal Hallucination Detector with Visual-aid Knowledge Base","created":"2025-02-18","cited_by_count":4,"area":"lr"},{"id":"2506.17587","title":"HalluRNN: Mitigating Hallucinations via Recurrent Cross-Layer Reasoning in Large Vision-Language Models","created":"2025-06-21","cited_by_count":4,"area":"lr"},{"id":"2510.10285","title":"Reallocating Attention Across Layers to Reduce Multimodal Hallucination","created":"2025-10-11","cited_by_count":4,"area":"lr"},{"id":"2602.15556","title":"Revealing and Enhancing Core Visual Regions: Harnessing Internal Attention Dynamics for Hallucination Mitigation in LVLMs","created":"2026-02-17","cited_by_count":4,"area":"lr"},{"id":"2606.27596","title":"Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding","created":"2026-06-25","cited_by_count":4,"area":"lr"},{"id":"2511.05017","title":"Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings","created":"2025-11-07","cited_by_count":3,"area":"lr"},{"id":"2603.17729","title":"SARE: Sample-wise Adaptive Reasoning for Training-free Fine-grained Visual Recognition","created":"2026-03-18","cited_by_count":3,"area":"lr"},{"id":"2603.27201","title":"Understanding and Mitigating Hallucinations in Multimodal Chain-of-Thought Models","created":"2026-03-28","cited_by_count":3,"area":"lr"},{"id":"2604.04863","title":"Beyond the Global Scores: Fine-Grained Token Grounding as a Robust Detector of LVLM Hallucinations","created":"2026-04-06","cited_by_count":3,"area":"lr"},{"id":"2608.08021","title":"Evidence-RL: Towards Evidence-intensive Visual Reasoning","created":"2026-08-08","cited_by_count":3,"area":"lr"},{"id":"2607.16303","title":"Med-OPD: Improving Medical Vision-Language Models via Evidence-Aware On-Policy Distillation","created":"2026-07-14","cited_by_count":2,"area":"lr"},{"id":"2609.06746","title":"Reason Through the Latent! Making Latent Visual Reasoning Necessary","created":"2026-09-06","cited_by_count":2,"area":"lr"},{"id":"2507.04943","title":"ReLoop: \"Seeing Twice and Thinking Backwards\" via Closed-loop Training to Mitigate Hallucinations in Multimodal understanding","created":"2025-07-07","cited_by_count":1,"area":"lr"},{"id":"2510.18424","title":"Med-VRAgent: A Framework for Medical Visual Reasoning-Enhanced Agents","created":"2025-10-21","cited_by_count":1,"area":"lr"},{"id":"2511.12446","title":"CoTBox-TTT: Grounding Medical VQA with Visual Chain-of-Thought Boxes During Test-time Training","created":"2025-11-16","cited_by_count":1,"area":"lr"},{"id":"2511.14106","title":"Stealth Fine-Tuning: Efficiently Breaking Alignment in RVLMs Using Self-Generated CoT","created":"2025-11-18","cited_by_count":1,"area":"lr"},{"id":"2602.14518","title":"Diagnosing Knowledge Conflict in Multimodal Long-Chain Reasoning","created":"2026-02-16","cited_by_count":1,"area":"lr"},{"id":"2602.19505","title":"Test-Time Computing for Referring Multimodal Large Language Models","created":"2026-02-23","cited_by_count":1,"area":"lr"},{"id":"2603.10978","title":"GroundCount: Grounding Vision-Language Models with Object Detection for Mitigating Counting Hallucinations","created":"2026-03-11","cited_by_count":1,"area":"lr"},{"id":"2604.10071","title":"Spotlight and Shadow: Attention-Guided Dual-Anchor Introspective Decoding for MLLM Hallucination Mitigation","created":"2026-04-11","cited_by_count":1,"area":"lr"},{"id":"2604.25809","title":"Instruction-Evidence Contrastive Dual-Stream Decoding for Grounded Vision-Language Reasoning","created":"2026-04-28","cited_by_count":1,"area":"lr"},{"id":"2605.11559","title":"When Looking Is Not Enough: Visual Attention Structure Reveals Hallucination in MLLMs","created":"2026-05-12","cited_by_count":1,"area":"lr"},{"id":"2607.01707","title":"LASER: A Corrective Lens for LVLMs via Visual Attention Preservation and Sink Suppression","created":"2026-07-02","cited_by_count":1,"area":"lr"},{"id":"2608.06938","title":"Debias in Text, Believe Your Eyes: Text-Anchored Cross-Modal Transfer for Visual Counter-Commonsense Reasoning","created":"2026-08-07","cited_by_count":1,"area":"lr"},{"id":"2507.07685","title":"Rationale-Enhanced Decoding for Multi-modal Chain-of-Thought","created":"2025-07-10","cited_by_count":0,"area":"lr"},{"id":"2509.23236","title":"Self-Consistency as a Free Lunch: Reducing Hallucinations in Vision-Language Models via Self-Reflection","created":"2025-09-27","cited_by_count":0,"area":"lr"},{"id":"2601.18356","title":"Making medical vision-language models think causally across modalities with retrieval-augmented cross-modal reasoning","created":"2026-01-26","cited_by_count":0,"area":"lr"},{"id":"2603.29405","title":"Hallucination-aware intermediate representation edit in large vision-language models","created":"2026-03-31","cited_by_count":0,"area":"lr"},{"id":"2605.07817","title":"GazeVLM: Active Vision via Internal Attention Control for Multimodal Reasoning","created":"2026-05-08","cited_by_count":0,"area":"lr"},{"id":"2605.27993","title":"Rethinking Visual Neglect: Steering via Context-Preference for MLLM Hallucination Mitigation","created":"2026-05-27","cited_by_count":0,"area":"lr"},{"id":"2607.00060","title":"Synergistic Perception-Reasoning Governance: Grounding Medical MLLMs with Verifiable Anatomical Evidence","created":"2026-06-30","cited_by_count":0,"area":"lr"},{"id":"2607.23944","title":"DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models","created":"2026-07-27","cited_by_count":0,"area":"lr"},{"id":"2607.25196","title":"Rethinking CD: A Reproducibility Study and Extension on the Ineffectiveness of Contrastive Decoding at Mitigating Object Hallucinations in MLLMs","created":"2026-07-28","cited_by_count":0,"area":"lr"},{"id":"2608.01207","title":"It's the Decoding Format, Not the Perturbation: Auditing Consistency-Based Selection for Vision-Language Test-Time Scaling","created":"2026-08-02","cited_by_count":0,"area":"lr"},{"id":"2608.09344","title":"Beyond Global Editing: Per-Instance Disentangled Subspaces for Training-Free Hallucination Mitigation in LVLMs","created":"2026-08-10","cited_by_count":0,"area":"lr"},{"id":"2608.10835","title":"UniProbe: A Learnable Token-Level Hallucination Detector for Large VLMs using Multi-Structural Internal Representations","created":"2026-08-11","cited_by_count":0,"area":"lr"},{"id":"2608.21305","title":"Re$^3$Cap: Retrieval-Guided Refinement for Image Captioning Enhancement via Reinforcement Learning","created":"2026-08-21","cited_by_count":0,"area":"lr"},{"id":"2609.09184","title":"Evidence-Order Calibration for Selective Visual Reasoning under Progressive Loss of Question-Critical Evidence","created":"2026-08-29","cited_by_count":0,"area":"lr"},{"id":"2609.16459","title":"OPD-Aha: From Linguistic Momentum to Visual Reflection in Multimodal On-Policy Distillation","created":"2026-09-15","cited_by_count":0,"area":"lr"},{"id":"2609.16601","title":"SAVOR: Self-Aware Visual Grounding via Confidence-Calibrated Reinforcement Learning for Multimodal Hallucination Mitigation","created":"2026-09-15","cited_by_count":0,"area":"lr"},{"id":"2609.24813","title":"INTCORT: Training-Free Spatial Reasoning Enhancement for Vision-Language Models via Input Transformations and Confidence Routing","created":"2026-09-21","cited_by_count":0,"area":"lr"},{"id":"2609.28570","title":"DEEPO: Dual-Entropy Enhanced Policy Optimization for Hallucination in MLLMs","created":"2026-09-23","cited_by_count":0,"area":"lr"},{"id":"2609.34905","title":"ReSight-SMC: Two-Stage Power Sampling via Island SMC with Visual Scouts","created":"2026-09-28","cited_by_count":0,"area":"lr"},{"id":"2609.36572","title":"Visual sensitivity is not claim retractability: persistence-aware credit assignment for multimodal reinforcement learning","created":"2026-09-29","cited_by_count":0,"area":"lr"},{"id":"2610.00333","title":"LEGO-OPD: Factorized Teacher Composition for Multimodal On-Policy Distillation","created":"2026-09-29","cited_by_count":0,"area":"lr"},{"id":"2610.04918","title":"Residual Visual Credit Optimization: Conserved Evidence Routing for Multimodal Reinforcement Learning","created":"2026-10-04","cited_by_count":0,"area":"lr"},{"id":"2610.05472","title":"Hallucination Across the Reasoning Lifecycle: Interface Visibility, Causal Evidence, and Release Control in Large Reasoning Models","created":"2026-10-04","cited_by_count":0,"area":"lr"}],"next_cursor":null}