{"total":108,"rows":[{"id":"2504.10479","title":"InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models","created":"2025-04-14","cited_by_count":1834,"area":null},{"id":"2509.17765","title":"Qwen3-Omni Technical Report","created":"2025-09-22","cited_by_count":497,"area":null},{"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":"2501.15368","title":"Baichuan-Omni-1.5 Technical Report","created":"2025-01-26","cited_by_count":111,"area":null},{"id":"2502.04328","title":"Ola: Pushing the Frontiers of Omni-Modal Language Model","created":"2025-02-06","cited_by_count":83,"area":null},{"id":"2507.07999","title":"Traceable Evidence Enhanced Visual Grounded Reasoning: Evaluation and Methodology","created":"2025-07-10","cited_by_count":69,"area":null},{"id":"2506.23044","title":"Ovis-U1 Technical Report","created":"2025-06-29","cited_by_count":67,"area":null},{"id":"2603.20633","title":"Seed1.8 Model Card: Towards Generalized Real-World Agency","created":"2026-03-21","cited_by_count":50,"area":null},{"id":"2504.04423","title":"UniToken: Harmonizing Multimodal Understanding and Generation through Unified Visual Encoding","created":"2025-04-06","cited_by_count":49,"area":null},{"id":"2504.14920","title":"DyFo: A Training-Free Dynamic Focus Visual Search for Enhancing LMMs in Fine-Grained Visual Understanding","created":"2025-04-21","cited_by_count":49,"area":null},{"id":"2410.08565","title":"Baichuan-Omni Technical Report","created":"2024-10-11","cited_by_count":42,"area":null},{"id":"2311.02782","title":"Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead","created":"2023-11-05","cited_by_count":40,"area":null},{"id":"2601.09668","title":"STEP3-VL-10B Technical Report","created":"2026-01-14","cited_by_count":32,"area":null},{"id":"2411.17673","title":"SketchAgent: Language-Driven Sequential Sketch Generation","created":"2024-11-26","cited_by_count":31,"area":null},{"id":"2504.18838","title":"Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks","created":"2025-04-26","cited_by_count":28,"area":null},{"id":"2510.06590","title":"Ming-UniVision: Joint Image Understanding and Generation with a Unified Continuous Tokenizer","created":"2025-10-08","cited_by_count":28,"area":null},{"id":"2412.18619","title":"Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey","created":"2024-12-16","cited_by_count":27,"area":null},{"id":"2503.01342","title":"UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface","created":"2025-03-03","cited_by_count":27,"area":null},{"id":"2601.21406","title":"Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation","created":"2026-01-29","cited_by_count":20,"area":null},{"id":"2411.16771","title":"VidHal: Benchmarking Temporal Hallucinations in Vision LLMs","created":"2024-11-25","cited_by_count":19,"area":null},{"id":"2412.05185","title":"LinVT: Empower Your Image-level Large Language Model to Understand Videos","created":"2024-12-06","cited_by_count":19,"area":null},{"id":"2502.18778","title":"M2-omni: Advancing Omni-MLLM for Comprehensive Modality Support with Competitive Performance","created":"2025-02-26","cited_by_count":19,"area":null},{"id":"2405.13684","title":"CrossCheckGPT: Universal Hallucination Ranking for Multimodal Foundation Models","created":"2024-05-22","cited_by_count":18,"area":null},{"id":"2511.03929","title":"NVIDIA Nemotron Nano V2 VL","created":"2025-11-06","cited_by_count":17,"area":null},{"id":"2503.19480","title":"GenHancer: Imperfect Generative Models are Secretly Strong Vision-Centric Enhancers","created":"2025-03-25","cited_by_count":16,"area":null},{"id":"2506.07371","title":"ARGUS: Hallucination and Omission Evaluation in Video-LLMs","created":"2025-06-09","cited_by_count":16,"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":"2504.01001","title":"Zero-shot Benchmarking: A Framework for Flexible and Scalable Automatic Evaluation of Language Models","created":"2025-04-01","cited_by_count":14,"area":null},{"id":"2509.22820","title":"MMPB: It's Time for Multi-Modal Personalization","created":"2025-09-26","cited_by_count":14,"area":null},{"id":"2403.00209","title":"ChartReformer: Natural Language-Driven Chart Image Editing","created":"2024-03-01","cited_by_count":13,"area":null},{"id":"2502.16435","title":"Human Cognitive Benchmarks Reveal Foundational Visual Gaps in MLLMs","created":"2025-02-23","cited_by_count":13,"area":null},{"id":"2505.02471","title":"Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction","created":"2025-05-05","cited_by_count":13,"area":null},{"id":"2407.14885","title":"Falcon2-11B Technical Report","created":"2024-07-20","cited_by_count":12,"area":null},{"id":"2503.01879","title":"Nexus: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision","created":"2025-02-26","cited_by_count":12,"area":null},{"id":"2412.02071","title":"Progress-Aware Video Frame Captioning","created":"2024-12-03","cited_by_count":11,"area":null},{"id":"2412.08169","title":"Illusory VQA: Benchmarking and Enhancing Multimodal Models on Visual Illusions","created":"2024-12-11","cited_by_count":11,"area":null},{"id":"2510.21356","title":"Gaze-VLM:Bridging Gaze and VLMs through Attention Regularization for Egocentric Understanding","created":"2025-10-24","cited_by_count":11,"area":null},{"id":"2605.20164","title":"Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR","created":"2026-05-19","cited_by_count":11,"area":null},{"id":"2502.11361","title":"VLDBench Evaluating Multimodal Disinformation with Regulatory Alignment","created":"2025-02-17","cited_by_count":9,"area":null},{"id":"2405.05363","title":"LOC-ZSON: Language-driven Object-Centric Zero-Shot Object Retrieval and Navigation","created":"2024-05-08","cited_by_count":8,"area":null},{"id":"2503.22215","title":"Learning to Instruct for Visual Instruction Tuning","created":"2025-03-28","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":"2604.21921","title":"Context Unrolling in Omni Models","created":"2026-04-23","cited_by_count":8,"area":null},{"id":"2502.15803","title":"Megrez-Omni Technical Report","created":"2025-02-19","cited_by_count":7,"area":null},{"id":"2507.22890","title":"Evaluating LLMs for Visualization Generation and Understanding","created":"2025-06-16","cited_by_count":5,"area":null},{"id":"2602.07064","title":"OmniFysics: Towards Physical Intelligence Evolution via Omni-Modal Signal Processing and Network Optimization","created":"2026-02-05","cited_by_count":5,"area":null},{"id":"2602.11488","title":"When Audio-LLMs Don't Listen: A Cross-Linguistic Study of Modality Arbitration","created":"2026-02-12","cited_by_count":5,"area":null},{"id":"2512.10652","title":"TriDF: Evaluating Perception, Detection, and Hallucination for Interpretable DeepFake Detection","created":"2025-12-11","cited_by_count":4,"area":null},{"id":"2603.11442","title":"GPT4o-Receipt: A Dataset and Human Study for AI-Generated Document Forensics","created":"2026-03-12","cited_by_count":4,"area":null},{"id":"2605.31604","title":"Representation Forcing for Bottleneck-Free Unified Multimodal Models","created":"2026-05-29","cited_by_count":4,"area":null},{"id":"2504.01792","title":"UniViTAR: Unified Vision Transformer with Native Resolution","created":"2025-04-02","cited_by_count":3,"area":null},{"id":"2506.07811","title":"Looking Beyond Visible Cues: Implicit Video Question Answering via Dual-Clue Reasoning","created":"2025-06-09","cited_by_count":3,"area":null},{"id":"2511.19199","title":"CLASH: A Benchmark for Cross-Modal Contradiction Detection","created":"2025-11-24","cited_by_count":3,"area":null},{"id":"2603.18373","title":"To See or To Please: Uncovering Visual Sycophancy and Split Beliefs in VLMs","created":"2026-03-19","cited_by_count":3,"area":null},{"id":"2605.13467","title":"PDCR: Perception-Decomposed Confidence Reward for Vision-Language Reasoning","created":"2026-05-13","cited_by_count":3,"area":null},{"id":"2503.24008","title":"H2VU-Benchmark: A Comprehensive Benchmark for Hierarchical Holistic Video Understanding","created":"2025-03-31","cited_by_count":2,"area":null},{"id":"2505.24517","title":"un$^2$CLIP: Improving CLIP's Visual Detail Capturing Ability via Inverting unCLIP","created":"2025-05-30","cited_by_count":2,"area":null},{"id":"2510.14792","title":"MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection","created":"2025-10-16","cited_by_count":2,"area":null},{"id":"2510.22784","title":"PIP-LLM: Integrating PDDL-Integer Programming with LLMs for Coordinating Multi-Robot Teams Using Natural Language","created":"2025-10-26","cited_by_count":2,"area":null},{"id":"2512.03405","title":"ViDiC: Video Difference Captioning","created":"2025-12-03","cited_by_count":2,"area":null},{"id":"2602.07625","title":"AD-MIR: Bridging the Gap from Perception to Persuasion in Advertising Video Understanding via Structured Reasoning","created":"2026-02-07","cited_by_count":2,"area":null},{"id":"2602.17768","title":"KPM-Bench: A Kinematic Parsing Motion Benchmark for Fine-grained Motion-centric Video Understanding","created":"2026-02-19","cited_by_count":2,"area":null},{"id":"2603.04803","title":"Guiding Diffusion-based Reconstruction with Contrastive Signals for Balanced Visual Representation","created":"2026-03-05","cited_by_count":2,"area":null},{"id":"2605.16403","title":"When Vision Speaks for Sound","created":"2026-05-13","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":"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":"2608.20958","title":"TLive-Omni: An Omni-Modal Understanding Model for E-Commerce Live Streaming","created":"2026-08-21","cited_by_count":2,"area":null},{"id":"2504.14429","title":"ResNetVLLM-2: Addressing ResNetVLLM's Multi-Modal Hallucinations","created":"2025-04-20","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":"2509.23109","title":"AttAnchor: Guiding Cross-Modal Token Alignment in VLMs with Attention Anchors","created":"2025-09-27","cited_by_count":1,"area":null},{"id":"2511.05883","title":"Unveiling Modality Bias: Automated Sample-Specific Analysis for Multimodal Misinformation Benchmarks","created":"2025-11-08","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":"2603.25711","title":"Seeing to Ground: Visual Attention for Hallucination-Resilient MDLLMs","created":"2026-03-26","cited_by_count":1,"area":null},{"id":"2605.15691","title":"SEED: Targeted Data Selection by Weighted Independent Set","created":"2026-05-15","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":"2606.03986","title":"NewtPhys: Do Foundation Models Understand Newtonian Physics?","created":"2026-06-02","cited_by_count":1,"area":null},{"id":"2606.24253","title":"TuringViT: Making SOTA Vision Transformers Accessible to All","created":"2026-06-23","cited_by_count":1,"area":null},{"id":"2606.32012","title":"CoMet: Context and Multiplicity Decomposition for Multimodal Uncertainty Estimation","created":"2026-06-30","cited_by_count":1,"area":null},{"id":"2412.06693","title":"OmniEvalKit: A Modular, Lightweight Toolbox for Evaluating Large Language Model and its Omni-Extensions","created":"2024-12-09","cited_by_count":0,"area":null},{"id":"2505.19529","title":"Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation","created":"2025-05-26","cited_by_count":0,"area":null},{"id":"2508.16527","title":"Towards Open World Detection: A Survey","created":"2025-08-22","cited_by_count":0,"area":null},{"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":"2602.11674","title":"Benchmark Health Index: A Systematic Framework for Benchmarking the Benchmarks of LLMs","created":"2026-02-12","cited_by_count":0,"area":null},{"id":"2603.20354","title":"Leum-VL Technical Report","created":"2026-03-20","cited_by_count":0,"area":null},{"id":"2603.24037","title":"A$^3$: Towards Advertising Aesthetic Assessment","created":"2026-03-25","cited_by_count":0,"area":null},{"id":"2603.29211","title":"Xuanwu: Evolving General Multimodal Models into an Industrial-Grade Foundation for Content Ecosystems","created":"2026-03-31","cited_by_count":0,"area":null},{"id":"2605.18714","title":"Semantic Generative Tuning for Unified Multimodal Models","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2606.01044","title":"Ask4VG: Risk-Aware Question Selection for Reducing Prior-Driven Answers in Medical VQA","created":"2026-05-31","cited_by_count":0,"area":null},{"id":"2607.23235","title":"A Reconstruction-Based Framework for Caption Evaluation Beyond Reference Captions","created":"2026-07-25","cited_by_count":0,"area":null},{"id":"2608.02589","title":"CAPEval: A Decoupled Caption Evaluation across Understanding and Generation","created":"2026-08-03","cited_by_count":0,"area":null},{"id":"2608.26495","title":"Video-FLAIR: Not Whether to Reason, But How","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2609.02277","title":"Auditory Illusion Benchmark for Large Audio Language Models","created":"2026-09-02","cited_by_count":0,"area":null},{"id":"2609.03426","title":"Lngram v2: Latent N-Gram Memory with Interpretable Discrete Representations","created":"2026-09-03","cited_by_count":0,"area":null},{"id":"2609.04801","title":"Whose record is this? Diagnosing and authorizing record use in personalized multimodal models","created":"2026-09-04","cited_by_count":0,"area":null},{"id":"2609.15229","title":"Pre-PEFT Probing: Weight Statistics and Perturbation Robustness for Layer Selection in VLM Vision Encoders","created":"2026-09-14","cited_by_count":0,"area":null},{"id":"2609.24881","title":"Pinocchio: Fast Uncertainty Estimates for Black-Box Language Models","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2609.25738","title":"OmniFysics-Nano-V2 Technical Report: Understanding the Physical World Across Modalities","created":"2026-09-22","cited_by_count":0,"area":null},{"id":"2609.29252","title":"IronViT: Toward Efficient Generalist Visual Representation Learning","created":"2026-09-24","cited_by_count":0,"area":null},{"id":"2609.29999","title":"GHOST-Q: Towards Studying Grounding Hallucinations Overlooked Under Same-score TradeOffs in Quantized VLMS","created":"2026-09-24","cited_by_count":0,"area":null},{"id":"2609.32763","title":"Mandela-Bench: Multimodal Models Remember Canonical Images Instead of Seeing Them","created":"2026-09-26","cited_by_count":0,"area":null}],"next_cursor":"100"}