作者位次 #4/5ICML 2026Poster· Deep Learning / Large Language Models
A Unified Approach to Interpreting Knowledge Distillation for Large Language Models via Interactions
Qingzhuo Wang · Ruiyang Qin · Zhenxin Qin · Wen Shen · Zhihua Wei
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Qingzhuo Wang · Ruiyang Qin · Zhenxin Qin · Wen Shen · Zhihua Wei
Ruiyang Qin · Qingzhuo Wang · Tian Wang · Zhihua Wei · Wen Shen
Zhenxin Qin · Qiang Li · Qingzhuo Wang · Ruiyang Qin · Zhihua Wei · Wen Shen
Large Vision-Language Models (LVLMs) have achieved remarkable performance on diverse vision-language tasks. However, LVLMs still suffer from hallucinations, generating text that contradicts the visual input. Existing research has primarily focused on mitigating object hallucinations, but often ov...
Junyao Yang · Chen Qian · Wen Shen · Yong Liu · Jing Shao · Dongrui Liu
Large Reasoning Models (LRMs) with long chain-of-thought reasoning have recently achieved remarkable success. Yet, equipping domain-specialized models with such reasoning capabilities, referred to as “Reasoning + X”, remains a significant challenge. While model merging offers a promising training...