Research · Monday 26 October 2026 · story 7
Paper describes Omni-Woodpecker for omni LLM hallucination correction
Huggingface reports a paper on Omni-Woodpecker, a training-free framework for omni LLMs that reduces cross-modal hallucinations by detecting conflicts across modalities and reweighting hidden representations. The abstract says Qwen2.5-Omni-7B gained 12.9 on CMM and 8.6 on AVHBench, while VideoLLaMA2-AV gained 4.6 and 3.9.
Why it matters. This gives omni agent builders a training-free option to cut cross-modal hallucinations on Qwen2.5-Omni-7B and VideoLLaMA2-AV.
Read the original at huggingface.co