Papers with modality reasoning gap

1 papers
Closing the Modality Reasoning Gap for Speech Large Language Models (2026.acl-long)

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Challenge: Recent advances in Speech Large Language Models have a modality reasoning gap that is not addressed by prior work.
Approach: They propose a reinforcement-learning framework that aligns text-conditioned and speech-conditioned trajectories through an asymmetric reward design.
Outcome: Experiments on MMSU and OBQA show that the proposed framework narrows the modality reasoning gap and achieves state-of-the-art performance among 7B-scale Speech LLMs.

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