{"total":81,"rows":[{"id":"2511.21631","title":"Qwen3-VL Technical Report","created":"2025-11-26","cited_by_count":2793,"area":"mllm"},{"id":"2604.15804","title":"Qwen3.5-Omni Technical Report","created":"2026-04-17","cited_by_count":174,"area":"moe"},{"id":"2501.00321","title":"OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning","created":"2024-12-31","cited_by_count":173,"area":"mllm"},{"id":"2509.01215","title":"POINTS-Reader: Distillation-Free Adaptation of Vision-Language Models for Document Conversion","created":"2025-09-01","cited_by_count":34,"area":"mllm"},{"id":"2601.09668","title":"STEP3-VL-10B Technical Report","created":"2026-01-14","cited_by_count":32,"area":null},{"id":"2505.19147","title":"Shifting AI Efficiency From Model-Centric to Data-Centric Compression","created":"2025-05-25","cited_by_count":29,"area":"mllm"},{"id":"2604.04771","title":"MinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scale","created":"2026-04-06","cited_by_count":27,"area":null},{"id":"2505.17163","title":"OCR-Reasoning Benchmark: Unveiling the True Capabilities of MLLMs in Complex Text-Rich Image Reasoning","created":"2025-05-22","cited_by_count":25,"area":"lr"},{"id":"2502.16161","title":"OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language Models","created":"2025-02-22","cited_by_count":23,"area":"lr"},{"id":"2504.11101","title":"Consensus Entropy: Harnessing Multi-VLM Agreement for Self-Verifying and Self-Improving OCR","created":"2025-04-15","cited_by_count":12,"area":"mllm"},{"id":"2506.20168","title":"Seeing is Believing? Mitigating OCR Hallucinations in Multimodal Large Language Models","created":"2025-06-25","cited_by_count":12,"area":"mllm"},{"id":"2601.02316","title":"DatBench: Discriminative, Faithful, and Efficient VLM Evaluations","created":"2026-01-05","cited_by_count":10,"area":null},{"id":"2601.20430","title":"Youtu-Parsing: Perception, Structuring and Recognition via High-Parallelism Decoding","created":"2026-01-28","cited_by_count":10,"area":null},{"id":"2607.24904","title":"Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model","created":"2026-07-27","cited_by_count":10,"area":"lr"},{"id":"2502.16586","title":"Multimodal Large Language Models for Text-rich Image Understanding: A Comprehensive Review","created":"2025-02-23","cited_by_count":9,"area":"mllm"},{"id":"2505.21771","title":"MMTABREAL: Real-World Benchmark for Multimodal Table Understanding","created":"2025-05-27","cited_by_count":9,"area":null},{"id":"2509.19768","title":"CHURRO: Making History Readable with an Open-Weight Large Vision-Language Model for High-Accuracy, Low-Cost Historical Text Recognition","created":"2025-09-24","cited_by_count":9,"area":null},{"id":"2510.16926","title":"Res-Bench: Benchmarking the Robustness of Multimodal Large Language Models to Dynamic Resolution Input","created":"2025-10-19","cited_by_count":9,"area":"mllm"},{"id":"2507.09861","title":"A Survey on MLLM-based Visually Rich Document Understanding: Methods, Challenges, and Emerging Trends","created":"2025-07-14","cited_by_count":8,"area":null},{"id":"2505.12766","title":"Reasoning-OCR: Can Large Multimodal Models Solve Complex Logical Reasoning Problems from OCR Cues?","created":"2025-05-19","cited_by_count":6,"area":"lr"},{"id":"2511.21750","title":"SO-Bench: A Structural Output Evaluation of Multimodal LLMs","created":"2025-11-23","cited_by_count":6,"area":"mllm"},{"id":"2512.10619","title":"DOCR-Inspector: Fine-Grained and Automated Evaluation of Document Parsing with VLM","created":"2025-12-11","cited_by_count":6,"area":null},{"id":"2505.20429","title":"PreP-OCR: A Complete Pipeline for Document Image Restoration and Enhanced OCR Accuracy","created":"2025-05-26","cited_by_count":5,"area":null},{"id":"2509.19345","title":"SCORE: A Semantic Evaluation Framework for Generative Document Parsing","created":"2025-09-16","cited_by_count":5,"area":null},{"id":"2511.04479","title":"ThaiOCRBench: A Task-Diverse Benchmark for Vision-Language Understanding in Thai","created":"2025-11-06","cited_by_count":5,"area":"mllm"},{"id":"2602.07038","title":"UNIKIE-BENCH: Benchmarking Large Multimodal Models for Key Information Extraction in Visual Documents","created":"2026-02-03","cited_by_count":5,"area":"mllm"},{"id":"2503.18484","title":"Benchmarking and Boosting Multilingual Capabilities of LVLMs via OCR-Centric Reinforcement Learning","created":"2025-03-24","cited_by_count":4,"area":"mllm"},{"id":"2505.12307","title":"LogicOCR: Do Your Large Multimodal Models Excel at Logical Reasoning on Text-Rich Images?","created":"2025-05-18","cited_by_count":4,"area":"lr"},{"id":"2601.12318","title":"Beyond Human Annotation: Recent Advances in Data Generation Methods for Document Intelligence","created":"2026-01-18","cited_by_count":4,"area":null},{"id":"2601.18735","title":"Why Keep Your Doubts to Yourself? Trading Visual Uncertainties in Multi-Agent Bandit Systems","created":"2026-01-26","cited_by_count":4,"area":"mllm"},{"id":"2506.11820","title":"Rethinking Multilingual Vision-Language Translation: Dataset, Evaluation, and Adaptation","created":"2025-06-13","cited_by_count":3,"area":"lr"},{"id":"2508.06009","title":"MathReal: We Keep It Real! A Real Scene Benchmark for Evaluating Math Reasoning in Multimodal Large Language Models","created":"2025-08-08","cited_by_count":3,"area":"lr"},{"id":"2604.00909","title":"JAMMEval: A Refined Collection of Japanese Benchmarks for Reliable VLM Evaluation","created":"2026-04-01","cited_by_count":3,"area":"mllm"},{"id":"2605.03903","title":"CC-OCR V2: Fine-Grained Attribution of LMM Failures in Real-World Visual Document Understanding","created":"2026-05-05","cited_by_count":3,"area":"mllm"},{"id":"2606.26122","title":"DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents","created":"2026-05-27","cited_by_count":3,"area":"agents"},{"id":"2508.10016","title":"Training-Free Multimodal Large Language Model Orchestration","created":"2025-08-06","cited_by_count":2,"area":"mllm"},{"id":"2511.14998","title":"FinCriticalED: A Visual Benchmark for Financial Fact-Level OCR","created":"2025-11-19","cited_by_count":2,"area":"mllm"},{"id":"2512.14114","title":"MFE-GAN: Efficient GAN-based Framework for Document Image Enhancement and Binarization with Multi-scale Feature Extraction","created":"2025-12-16","cited_by_count":2,"area":null},{"id":"2602.21042","title":"OmniOCR: Generalist OCR for Ethnic Minority Languages","created":"2026-02-24","cited_by_count":2,"area":null},{"id":"2603.15409","title":"SEA-Vision: A Multilingual Benchmark for Comprehensive Document and Scene Text Understanding in Southeast Asia","created":"2026-03-16","cited_by_count":2,"area":null},{"id":"2604.12978","title":"GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts","created":"2026-04-14","cited_by_count":2,"area":"mllm"},{"id":"2605.11301","title":"LatentRouter: Can We Choose the Right Multimodal Model Before Seeing Its Answer?","created":"2026-05-11","cited_by_count":2,"area":"lr"},{"id":"2606.01348","title":"ChartArena: Benchmarking Chart Parsing across Languages, Scenarios, and Formats","created":"2026-05-31","cited_by_count":2,"area":null},{"id":"2606.29905","title":"StrucTab: A Structured Optimization Framework for Table Parsing","created":"2026-06-29","cited_by_count":2,"area":null},{"id":"2607.02956","title":"MORE: A Multilingual Document Parsing Benchmark and Evaluation","created":"2026-07-03","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":"2609.02401","title":"CA-OPD: Confidence-Aware On-Policy Distillation for Structured Visual Prediction","created":"2026-09-02","cited_by_count":2,"area":"mllm"},{"id":"2505.23265","title":"SPR-128K: A New Benchmark for Spatial Plausibility Reasoning with Multimodal Large Language Models","created":"2025-05-29","cited_by_count":1,"area":"lr"},{"id":"2509.03615","title":"E-ARMOR: Edge case Assessment and Review of Multilingual Optical Character Recognition","created":"2025-09-03","cited_by_count":1,"area":null},{"id":"2509.06415","title":"Index-Preserving Lightweight Token Pruning for Efficient Document Understanding in Vision-Language Models","created":"2025-09-08","cited_by_count":1,"area":"mllm"},{"id":"2510.21849","title":"TowerVision: Understanding and Improving Multilinguality in Vision-Language Models","created":"2025-10-22","cited_by_count":1,"area":"mllm"},{"id":"2511.10055","title":"Physical Plausibility Reasoning via HCM-GRPO: Empowering Compact Model for Superior Performance","created":"2025-11-13","cited_by_count":1,"area":"lr"},{"id":"2603.22819","title":"TDATR: Improving End-to-End Table Recognition via Table Detail-Aware Learning and Cell-Level Visual Alignment","created":"2026-03-24","cited_by_count":1,"area":null},{"id":"2605.22100","title":"MPDocBench-Parse: Benchmarking Practical Multi-page Document Parsing","created":"2026-05-21","cited_by_count":1,"area":null},{"id":"2605.26712","title":"METATR: A Multilingual, Evolving Benchmark for Automatic Text Recognition","created":"2026-05-26","cited_by_count":1,"area":null},{"id":"2607.04636","title":"Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis","created":"2026-07-06","cited_by_count":1,"area":"mllm"},{"id":"2609.03445","title":"OCR-EDR: Rendering-Aware Diagnosis and Repair for Closed-Loop OCR Improvement","created":"2026-09-03","cited_by_count":1,"area":null},{"id":"2609.24058","title":"All-in-One Multilingual Scene Text Recognition with Script-aware Mixture-of-Experts","created":"2026-09-21","cited_by_count":1,"area":"moe"},{"id":"2412.16455","title":"Research on Violent Text Detection System Based on BERT-fasttext Model","created":"2024-12-21","cited_by_count":0,"area":null},{"id":"2505.10055","title":"PsOCR: Benchmarking Large Multimodal Models for Optical Character Recognition in Low-resource Pashto Language","created":"2025-05-15","cited_by_count":0,"area":"mllm"},{"id":"2510.21774","title":"OCR-Quality: A Human-Annotated Dataset for OCR Quality Assessment","created":"2025-10-17","cited_by_count":0,"area":null},{"id":"2601.10104","title":"MathDoc: Benchmarking Structured Extraction and Active Refusal on Noisy Mathematics Exam Papers","created":"2026-01-15","cited_by_count":0,"area":null},{"id":"2602.03693","title":"OCRTurk: A Comprehensive OCR Benchmark for Turkish","created":"2026-02-03","cited_by_count":0,"area":"rag"},{"id":"2603.27942","title":"JaWildText: A Benchmark for Vision-Language Models on Japanese Scene Text Understanding","created":"2026-03-30","cited_by_count":0,"area":"mllm"},{"id":"2604.02048","title":"Jagle: Building a Large-Scale Japanese Multimodal Post-Training Dataset for Vision-Language Models","created":"2026-04-02","cited_by_count":0,"area":"mllm"},{"id":"2604.03553","title":"Chronos: The AI Co-Historian","created":"2026-04-04","cited_by_count":0,"area":null},{"id":"2605.30265","title":"LoMo: Local Modality Substitution for Deeper Vision-Language Fusion","created":"2026-05-28","cited_by_count":0,"area":"mllm"},{"id":"2606.11477","title":"Towards Fully Automated Exam Grading: Fairness-Aware Recognition of Handwritten Answers with Foundation Models","created":"2026-06-09","cited_by_count":0,"area":null},{"id":"2606.19096","title":"PorTEXTO: A European Portuguese Benchmark for Visual Text Extraction","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2608.09842","title":"From Diagnosis to Correction: Benchmarking and Improving Real-World Table Parsing","created":"2026-08-10","cited_by_count":0,"area":null},{"id":"2608.18586","title":"OmniHandwritingOCR: A Diagnostic Benchmark for Evaluating Multimodal LLMs in Handwritten OCR Scenarios","created":"2026-08-19","cited_by_count":0,"area":"mllm"},{"id":"2608.20122","title":"ArmorOCR: Grounded Adversarial Visual Perception via Observation-Transferred Self-Distillation","created":"2026-08-20","cited_by_count":0,"area":"mllm"},{"id":"2608.27169","title":"Ancient-Bench: A Comprehensive Multi-millennial, Multi-medium, and Multi-script Benchmark for Ancient Chinese Artifact Text Recognition","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2608.28248","title":"Synth-JDoc: Synthesizing a Japanese Document Image Dataset for OCR with Diverse Layouts and Embedded Images","created":"2026-08-28","cited_by_count":0,"area":"mllm"},{"id":"2609.01575","title":"Closing Cost-Quality Gap in Document VLMs: Difficulty-Aware Data Curation and Quality-Adjusted Deployment Economics","created":"2026-09-01","cited_by_count":0,"area":null},{"id":"2609.21351","title":"PrismAlign: Prior-Steered Multi-View VLM Alignment for Hallucination-Robust Table OCR","created":"2026-09-18","cited_by_count":0,"area":null},{"id":"2609.24092","title":"DocMIDE: Learning Multi-Hop Implicit Derivation in Visually Rich Documents","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2609.31103","title":"DepthEvidence: Unifying Metric Depth Prediction and Geometric Reasoning in Multimodal Language Models","created":"2026-09-25","cited_by_count":0,"area":"lr"},{"id":"2609.37712","title":"PolyOCR-Venus: Unified OCR Foundation Models for Text-Centric Visual Intelligence","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.11148","title":"SP-DocReader: Difference-Aware Self-Play for Precise Document OCR","created":"2026-10-08","cited_by_count":0,"area":"mllm"},{"id":"2610.20461","title":"Equal CER, Unequal Damage: Severity-Weighted Character Error Rate for OCR","created":"2026-10-14","cited_by_count":0,"area":"mllm"}],"next_cursor":null}