Papers with OLLM

1 papers
Investigating and Enhancing Vision-Audio Capability in Omnimodal Large Language Models (2025.findings-acl)

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Challenge: Recent years have witnessed significant advancements in large language models (LLMs) but still struggle with integrating vision and audio.
Approach: They propose a self-knowledge distillation method to improve vision-audio capabilities of OLLMs by learning from the vision-text components.
Outcome: The proposed method improves vision-audio capabilities of OLLMs by learning from vision-text components, which improves interaction between audio and images and results in improved performance on multimodal tasks.

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