Papers with text-only reasoning

2 papers
Flexible Thinking for Multimodal Emotional Support Conversation via Reinforcement Learning (2025.findings-emnlp)

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Challenge: Current Chain-of-Thought based ESC methods often employ rigid, text-only reasoning, limiting adaptability in dynamic, multimodal interactions and introducing reasoning noise that degrades support quality.
Approach: They propose a framework that integrates supervised fine-tuning with reinforcement learning to improve ESC models' response quality.
Outcome: The proposed framework enables models to select contextually relevant thinking aspects: Visual Scene, Emotion, Situation, and Response Strategy.
Reasoning in the Dark: Interleaved Vision-Text Reasoning in Latent Space (2026.findings-acl)

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Challenge: Existing multimodal reasoning methods depend on explicit reasoning steps that require labor-intensive vision-text annotations and inherently introduce significant inference latency.
Approach: They propose a method that integrates visual and visual information into the reasoning process to improve the performance of multimodal LLMs.
Outcome: The proposed method achieves an average performance increase of 5.45% while achieving a speed increase of over 5 times compared to existing methods.

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