Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey
Official implementation of GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents
A Comprehensive Survey on Evaluating Reasoning Capabilities in Multimodal Large Language Models.
(ArXiv25) Vision Matters: Simple Visual Perturbations Can Boost Multimodal Math Reasoning
[ACL 2025] FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation
🔥🔥🔥Latest Papers, Codes on Uncertainty-based RL
[CVPR 2025] Code for "Notes-guided MLLM Reasoning: Enhancing MLLM with Knowledge and Visual Notes for Visual Question Answering".
A Multimodal Benchmark for Evaluating Scientific Reasoning Capabilities of VLMs
Enhancing Step-by-Step and Verifiable Medical Reasoning in MLLMs
We introduce the YesBut-v2, a benchmark for assessing AI's ability to interpret juxtaposed comic panels with contradictory narratives. Unlike existing benchmarks, it emphasizes visual understanding, comparative reasoning, and social knowledge.
NoteMR enhances multimodal large language models for visual question answering by integrating structured notes. This implementation aims to reduce reasoning errors and improve visual feature perception. 🐙📚
Vision Matters explores how simple visual changes can enhance multimodal math reasoning. Join the discussion and contribute to the project! 👩💻👨💻
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