Papers with visual reasoning capability

1 papers
MDocRAG-RL: Empowering Multi-Modal Document RAG via Complex Visual Reasoning with Reinforcement Learning (2026.findings-acl)

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Challenge: Existing RAG systems produce suboptimal embeddings and naively insert images into context without adequate visual perception, limiting reasoning capabilities.
Approach: They propose a novel RAG framework for complex visual reasoning that integrates multimodal large language models with external knowledge to enhance retrieval efficiency.
Outcome: The proposed framework achieves state-of-the-art performance on multiple benchmarks.

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