{"total":53,"rows":[{"id":"2402.17177","title":"Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models","created":"2024-02-27","cited_by_count":477,"area":null},{"id":"2503.22679","title":"Q-Insight: Understanding Image Quality via Visual Reinforcement Learning","created":"2025-03-28","cited_by_count":98,"area":null},{"id":"2404.07973","title":"Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models","created":"2024-04-11","cited_by_count":97,"area":null},{"id":"2410.10818","title":"TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models","created":"2024-10-14","cited_by_count":97,"area":null},{"id":"2406.08478","title":"What If We Recaption Billions of Web Images with LLaMA-3?","created":"2024-06-12","cited_by_count":87,"area":null},{"id":"2406.06040","title":"Vript: A Video Is Worth Thousands of Words","created":"2024-06-10","cited_by_count":71,"area":null},{"id":"2506.17221","title":"VLN-R1: Vision-Language Navigation via Reinforcement Fine-Tuning","created":"2025-06-20","cited_by_count":63,"area":null},{"id":"2406.07502","title":"Image Textualization: An Automatic Framework for Creating Accurate and Detailed Image Descriptions","created":"2024-06-11","cited_by_count":43,"area":null},{"id":"2509.12886","title":"The LLM Already Knows: Estimating LLM-Perceived Question Difficulty via Hidden Representations","created":"2025-09-16","cited_by_count":29,"area":null},{"id":"2405.03194","title":"CityLLaVA: Efficient Fine-Tuning for VLMs in City Scenario","created":"2024-05-06","cited_by_count":27,"area":null},{"id":"2505.24535","title":"Beyond Linear Steering: Unified Multi-Attribute Control for Language Models","created":"2025-05-30","cited_by_count":25,"area":null},{"id":"2403.08192","title":"MoleculeQA: A Dataset to Evaluate Factual Accuracy in Molecular Comprehension","created":"2024-03-13","cited_by_count":22,"area":null},{"id":"2506.19848","title":"ScaleCap: Inference-Time Scalable Image Captioning via Dual-Modality Debiasing","created":"2025-06-24","cited_by_count":15,"area":null},{"id":"2511.20351","title":"Thinking in 360{\\deg}: Humanoid Visual Search in the Wild","created":"2025-11-25","cited_by_count":15,"area":null},{"id":"2410.02740","title":"Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models","created":"2024-10-03","cited_by_count":14,"area":null},{"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":"2604.19632","title":"CreatiParser: Generative Image Parsing of Raster Graphic Designs into Editable Layers","created":"2026-04-21","cited_by_count":9,"area":null},{"id":"2410.15359","title":"Hallucination in Multimodal Foundation Models: A Survey on Causes, Corrections, and Evaluations","created":"2024-10-20","cited_by_count":8,"area":null},{"id":"2505.20873","title":"Fork-Merge Decoding: Enhancing Multimodal Understanding in Audio-Visual Large Language Models","created":"2025-05-27","cited_by_count":8,"area":null},{"id":"2410.13754","title":"MixEval-X: Any-to-Any Evaluations from Real-World Data Mixtures","created":"2024-10-17","cited_by_count":6,"area":null},{"id":"2504.07901","title":"Redefining Machine Translation on Social Network Services with Large Language Models","created":"2025-04-10","cited_by_count":6,"area":null},{"id":"2512.05671","title":"ClinTutor-R1: Advancing Scalable and Robust One-to-Many Alignment in Clinical Socratic Education","created":"2025-12-05","cited_by_count":6,"area":null},{"id":"2407.16160","title":"UniMEL: A Unified Framework for Multimodal Entity Linking with Large Language Models","created":"2024-07-23","cited_by_count":5,"area":null},{"id":"2506.11111","title":"Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions","created":"2025-06-08","cited_by_count":5,"area":null},{"id":"2605.10815","title":"Probing Cross-modal Information Hubs in Audio-Visual LLMs","created":"2026-05-11","cited_by_count":5,"area":null},{"id":"2506.13888","title":"VL-GenRM: Enhancing Vision-Language Verification via Vision Experts and Iterative Training","created":"2025-06-16","cited_by_count":4,"area":null},{"id":"2508.03296","title":"Towards Trustworthy Multimodal Moderation via Policy-Aligned Reasoning and Hierarchical Labeling","created":"2025-08-05","cited_by_count":4,"area":null},{"id":"2604.21718","title":"Building a Precise Video Language with Human-AI Oversight","created":"2026-04-22","cited_by_count":3,"area":null},{"id":"2410.15460","title":"Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training","created":"2024-10-20","cited_by_count":2,"area":null},{"id":"2502.05242","title":"Beyond External Monitors: Enhancing Transparency of Large Language Models for Easier Monitoring","created":"2025-02-07","cited_by_count":2,"area":null},{"id":"2606.01717","title":"Decentralized Instruction Tuning: Conflict-Aware Splitting and Weight Merging","created":"2026-06-01","cited_by_count":2,"area":null},{"id":"2608.07565","title":"What to Edit Next: Visually Aligned Image-Editing Follow-Up Suggestions in Conversational Systems","created":"2026-08-03","cited_by_count":2,"area":null},{"id":"2501.02842","title":"Foundations of GenIR","created":"2025-01-06","cited_by_count":1,"area":null},{"id":"2505.05074","title":"Visual Affordance Prediction: Survey and Reproducibility","created":"2025-05-08","cited_by_count":1,"area":null},{"id":"2506.08486","title":"RHealthTwin: Towards Responsible and Multimodal Digital Twins for Personalized Well-being","created":"2025-06-10","cited_by_count":1,"area":null},{"id":"2508.07388","title":"Invert4TVG: A Temporal Video Grounding Framework with Inversion Tasks Preserving Action Understanding Ability","created":"2025-08-10","cited_by_count":1,"area":null},{"id":"2509.01610","title":"Improving Large Vision and Language Models by Learning from a Panel of Peers","created":"2025-09-01","cited_by_count":1,"area":null},{"id":"2509.03957","title":"CANDY: Benchmarking LLMs' Limitations and Assistive Potential in Chinese Misinformation Fact-Checking","created":"2025-09-04","cited_by_count":1,"area":null},{"id":"2511.00220","title":"Iterative Foundation Model Fine-Tuning on Multiple Rewards","created":"2025-10-31","cited_by_count":1,"area":null},{"id":"2603.14880","title":"RealVLG-R1: A Large-Scale Real-World Visual-Language Grounding Benchmark for Robotic Perception and Manipulation","created":"2026-03-16","cited_by_count":1,"area":null},{"id":"2604.08209","title":"OmniJigsaw: Enhancing Omni-Modal Reasoning via Modality-Orchestrated Reordering","created":"2026-04-09","cited_by_count":1,"area":null},{"id":"2605.28023","title":"VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning","created":"2026-05-27","cited_by_count":1,"area":null},{"id":"2507.11502","title":"HKGAI-V1: Towards Regional Sovereign Large Language Model for Hong Kong","created":"2025-07-14","cited_by_count":0,"area":null},{"id":"2508.06443","title":"The Fair Game: Auditing & Debiasing AI Algorithms Over Time","created":"2025-08-08","cited_by_count":0,"area":null},{"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":"2605.02200","title":"ARGUS: Policy-Adaptive Ad Governance via Evolving Reinforcement with Adversarial Umpiring","created":"2026-05-04","cited_by_count":0,"area":null},{"id":"2606.00819","title":"Mitigating Hallucinations in Large Language Models Via Decoder Layer Skipping","created":"2026-05-30","cited_by_count":0,"area":null},{"id":"2606.09249","title":"DECIS: Dual-Evidence Corrective Verification for Interpretable Strabismus Diagnostic Decision-Making","created":"2026-06-08","cited_by_count":0,"area":null},{"id":"2608.00502","title":"SpatialAfford: Teaching Compact VLMs Where to Look and Where to Ground for Affordance","created":"2026-08-01","cited_by_count":0,"area":null},{"id":"2609.15051","title":"Not All Prompts Are Equal: Exploration-Guided Prompt Scaffolding for Multimodal Reinforcement Post-Training","created":"2026-09-14","cited_by_count":0,"area":null},{"id":"2610.02999","title":"OmniConfess: Eliciting Token Confessions to Mitigate Omni-Modal Hallucination","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.16735","title":"VAttnPO: Visual Attention-Guided Policy Optimization","created":"2026-10-12","cited_by_count":0,"area":null},{"id":"2610.18141","title":"Mitigating Cross-Modal Hallucinations by Correcting Modality Misrouting in Omnimodal LLMs","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}