揭秘MoE模型中的知识注入，专家感知对比解码有效缓解大模型幻觉！
arXiv:2607.20426v1 Announce Type: cross Abstract: Existing LLM hallucination mitigation methods, including prompt engineering and model optimization, …
从上下文感知升级到冲突感知，泛化对比解码解决LLM知识冲突，提升模型可靠性。
arXiv:2606.10298v1 Announce Type: new Abstract: When large language models generate from retrieved or augmented contexts, conflicts between external c…
利用反事实数据实现模型感知的对比解码，让文本生成质量与真实性同步提升。
arXiv:2602.01740v3 Announce Type: replace Abstract: Video language models (Video-LLMs) are prone to hallucinations, generating plausible but ungrounde…
揭示对比解码在降低多模态大模型对象幻觉上的无效性，颠覆普遍认知，值得研究者警惕。
arXiv:2504.10020v4 Announce Type: replace-cross Abstract: Contrastive decoding strategies are widely used to reduce object hallucinations in multimoda…