Papers with direct reasoning training approach

1 papers
GeoPQA: Bridging the Visual Perception Gap in MLLMs for Geometric Reasoning (2025.findings-emnlp)

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Challenge: Recent advances in reinforcement learning (RL) have enhanced the reasoning abilities of large language models, but the impact on multimodal LLMs is limited.
Approach: They propose a two-stage RL framework that enhances visual perception and fosters reasoning capabilities.
Outcome: The proposed framework improves geometric reasoning by 9.7% and problem-solving by 9.1% compared to direct reasoning training approach.

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