{"total":69,"rows":[{"id":"2407.11691","title":"VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models","created":"2024-07-16","cited_by_count":455,"area":null},{"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":"2505.19255","title":"VTool-R1: VLMs Learn to Think with Images via Reinforcement Learning on Multimodal Tool Use","created":"2025-05-25","cited_by_count":90,"area":"lr"},{"id":"2501.05452","title":"ReFocus: Visual Editing as a Chain of Thought for Structured Image Understanding","created":"2025-01-09","cited_by_count":83,"area":"lr"},{"id":"2502.14846","title":"Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation","created":"2025-02-20","cited_by_count":58,"area":"mllm"},{"id":"2510.26802","title":"Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmark","created":"2025-10-30","cited_by_count":43,"area":"lr"},{"id":"2501.03225","title":"Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation","created":"2025-01-06","cited_by_count":30,"area":"mllm"},{"id":"2505.18129","title":"One RL to See Them All: Visual Triple Unified Reinforcement Learning","created":"2025-05-23","cited_by_count":30,"area":"lr"},{"id":"2508.03404","title":"Visual Document Understanding and Reasoning: A Multi-Agent Collaboration Framework with Agent-Wise Adaptive Test-Time Scaling","created":"2025-08-05","cited_by_count":30,"area":"lr"},{"id":"2409.18142","title":"A Survey on Multimodal Benchmarks: In the Era of Large AI Models","created":"2024-09-21","cited_by_count":27,"area":"mllm"},{"id":"2505.11015","title":"WildDoc: How Far Are We from Achieving Comprehensive and Robust Document Understanding in the Wild?","created":"2025-05-16","cited_by_count":26,"area":"mllm"},{"id":"2407.07053","title":"Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model","created":"2024-07-09","cited_by_count":21,"area":"lr"},{"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":"2506.04088","title":"Multimodal Tabular Reasoning with Privileged Structured Information","created":"2025-06-04","cited_by_count":15,"area":"lr"},{"id":"2505.22946","title":"NegVQA: Can Vision Language Models Understand Negation?","created":"2025-05-28","cited_by_count":13,"area":"mllm"},{"id":"2506.13405","title":"RealHiTBench: A Comprehensive Realistic Hierarchical Table Benchmark for Evaluating LLM-Based Table Analysis","created":"2025-06-16","cited_by_count":12,"area":null},{"id":"2602.22766","title":"Imagination Helps Visual Reasoning, But Not Yet in Latent Space","created":"2026-02-26","cited_by_count":12,"area":"lr"},{"id":"2601.03872","title":"Atlas: Orchestrating Heterogeneous Models and Tools for Multi-Domain Complex Reasoning","created":"2026-01-07","cited_by_count":11,"area":"lr"},{"id":"2408.13860","title":"Knowledge-Aware Reasoning over Multimodal Semi-structured Tables","created":"2024-08-25","cited_by_count":9,"area":null},{"id":"2502.01341","title":"AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding","created":"2025-02-03","cited_by_count":9,"area":"mllm"},{"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":"2505.14071","title":"Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models","created":"2025-05-20","cited_by_count":9,"area":"mllm"},{"id":"2511.18434","title":"DocPTBench: Benchmarking End-to-End Photographed Document Parsing and Translation","created":"2025-11-23","cited_by_count":9,"area":"mllm"},{"id":"2606.10400","title":"Do Vision-Language Models See or Guess? Measuring and Reducing Textual-Prior Reliance with a Phrasing-Controlled Benchmark","created":"2026-06-09","cited_by_count":8,"area":"mllm"},{"id":"2412.04531","title":"MageBench: Bridging Large Multimodal Models to Agents","created":"2024-12-05","cited_by_count":6,"area":"mllm"},{"id":"2502.17315","title":"HIPPO: Enhancing the Table Understanding Capability of LLMs through Hybrid-Modal Preference Optimization","created":"2025-02-24","cited_by_count":6,"area":"alignment"},{"id":"2509.07966","title":"Visual-TableQA: Open-Domain Benchmark for Reasoning over Table Images","created":"2025-09-09","cited_by_count":6,"area":"lr"},{"id":"2509.21205","title":"TABLET: A Large-Scale Dataset for Robust Visual Table Understanding","created":"2025-09-25","cited_by_count":5,"area":null},{"id":"2510.09671","title":"Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation","created":"2025-10-08","cited_by_count":5,"area":null},{"id":"2603.20194","title":"MME-CoF-Pro: Evaluating Reasoning Coherence in Video Generative Models with Text and Visual Hints","created":"2026-03-20","cited_by_count":5,"area":"lr"},{"id":"2605.05668","title":"Large Vision-Language Models Get Lost in Attention","created":"2026-05-07","cited_by_count":5,"area":"mllm"},{"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":"2504.09249","title":"NoTeS-Bank: Benchmarking Neural Transcription and Search for Scientific Notes Understanding","created":"2025-04-12","cited_by_count":3,"area":null},{"id":"2506.18421","title":"TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models","created":"2025-06-23","cited_by_count":3,"area":"lr"},{"id":"2605.08146","title":"VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning","created":"2026-05-03","cited_by_count":3,"area":null},{"id":"2410.00773","title":"BabelBench: An Omni Benchmark for Code-Driven Analysis of Multimodal and Multistructured Data","created":"2024-10-01","cited_by_count":2,"area":null},{"id":"2507.10281","title":"Toward Real-World Table Agents: Capabilities, Workflows, and Design Principles for LLM-based Table Intelligence","created":"2025-07-14","cited_by_count":2,"area":"agents"},{"id":"2508.15690","title":"GRAFT: GRaPH and Table Reasoning for Textual Alignment -- A Benchmark for Structured Instruction Following and Visual Reasoning","created":"2025-08-21","cited_by_count":2,"area":"lr"},{"id":"2508.17334","title":"Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMs","created":"2025-08-24","cited_by_count":2,"area":"mllm"},{"id":"2510.07098","title":"TALENT: Table VQA via Augmented Language-Enhanced Natural-text Transcription","created":"2025-10-08","cited_by_count":2,"area":"mllm"},{"id":"2602.15257","title":"How to Train Your Long-Context Visual Document Model","created":"2026-02-16","cited_by_count":2,"area":"mllm"},{"id":"2608.22429","title":"Think with Structured Grounding: Perceptual Reinforcement Learning for Chart and Visual-Tabular Understanding","created":"2026-08-23","cited_by_count":2,"area":"lr"},{"id":"2504.09979","title":"Resampling Benchmark for Efficient Comprehensive Evaluation of Large Vision-Language Models","created":"2025-04-14","cited_by_count":1,"area":"mllm"},{"id":"2504.20047","title":"HCT-QA: A Benchmark for Question Answering on Human-Centric Tables","created":"2025-03-09","cited_by_count":1,"area":null},{"id":"2506.14805","title":"Argus Inspection: Do Multimodal Large Language Models Possess the Eye of Panoptes?","created":"2025-06-03","cited_by_count":1,"area":"lr"},{"id":"2507.11694","title":"ExpliCIT-QA: Explainable Code-Based Image Table Question Answering","created":"2025-07-15","cited_by_count":1,"area":null},{"id":"2511.06582","title":"TabRAG: Improving Tabular Document Question Answering for Retrieval Augmented Generation via Structured Representations","created":"2025-11-10","cited_by_count":1,"area":"rag"},{"id":"2605.01018","title":"WildTableBench: Benchmarking Multimodal Foundation Models on Table Understanding In the Wild","created":"2026-05-01","cited_by_count":1,"area":null},{"id":"2605.05955","title":"TableVista: Benchmarking Multimodal Table Reasoning under Visual and Structural Complexity","created":"2026-05-07","cited_by_count":1,"area":null},{"id":"2605.08138","title":"DataArc-SynData-Toolkit: A Unified Closed-Loop Framework for Multi-Path, Multimodal, and Multilingual Data Synthesis","created":"2026-05-02","cited_by_count":1,"area":"synth"},{"id":"2606.09578","title":"TABVERSE: Benchmarking Cross-Format Table Understanding in LLMs and VLMs","created":"2026-06-08","cited_by_count":1,"area":"mllm"},{"id":"2607.10966","title":"SVR-R1: Bootstrapping Multi-modal Reasoning with Self-verification in Reinforcement Learning","created":"2026-07-13","cited_by_count":1,"area":"lr"},{"id":"2607.19790","title":"Trace: A Taxonomy-Guided Environment for Multidomain Visual Reasoning","created":"2026-07-22","cited_by_count":1,"area":"lr"},{"id":"2608.08557","title":"OpenVisTool: An Open Recipe for Synthesizing Instructive Visual Tool-Use Trajectories","created":"2026-08-09","cited_by_count":1,"area":null},{"id":"2609.10494","title":"IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier","created":"2026-09-09","cited_by_count":1,"area":null},{"id":"2507.08575","title":"Large Multi-modal Model Cartographic Map Comprehension for Textual Locality Georeferencing","created":"2025-07-11","cited_by_count":0,"area":"mllm"},{"id":"2602.19188","title":"PositionOCR: Augmenting Positional Awareness in Multi-Modal Models via Hybrid Specialist Integration","created":"2026-02-22","cited_by_count":0,"area":"mllm"},{"id":"2604.02371","title":"Internalized Reasoning for Long-Context Visual Document Understanding","created":"2026-03-31","cited_by_count":0,"area":null},{"id":"2604.03660","title":"TableVision: A Large-Scale Benchmark for Spatially Grounded Reasoning over Complex Hierarchical Tables","created":"2026-04-04","cited_by_count":0,"area":"lr"},{"id":"2604.11970","title":"INDOTABVQA: A Benchmark for Cross-Lingual Table Understanding in Bahasa Indonesia Documents","created":"2026-04-13","cited_by_count":0,"area":null},{"id":"2604.16099","title":"DenTab: A Dataset for Table Recognition and Visual QA on Real-World Dental Estimates","created":"2026-04-17","cited_by_count":0,"area":null},{"id":"2606.11652","title":"IAPO: Input Attribution-Aware Policy Optimization for Tool Use in Small Multimodal Agents","created":"2026-06-10","cited_by_count":0,"area":"agents"},{"id":"2606.26041","title":"How Robust is OCR-Reasoning? Evaluating OCR-Reasoning Robustness of Vision-Language Models under Visual Perturbations","created":"2026-06-24","cited_by_count":0,"area":"lr"},{"id":"2608.00013","title":"What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs","created":"2026-06-24","cited_by_count":0,"area":"mllm"},{"id":"2608.20840","title":"KoViDoRe: A Benchmark for Korean Visual Document Retrieval","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2608.26949","title":"A Table Is Worth 64 Tokens: Pixel-level Compression for Multi-Table Document Question Answering","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2608.29037","title":"DocIntent: Answerability-Guided Agentic Restoration for Real-World Document Visual Question Answering","created":"2026-08-29","cited_by_count":0,"area":"mllm"},{"id":"2609.17458","title":"Tables Decoded: DELTA for Structure, TARQA for Understanding","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2610.07018","title":"When to Rethink: Learning Multi-Perspective Self-Verification for Vision-Language Models","created":"2026-10-04","cited_by_count":0,"area":"lr"}],"next_cursor":null}