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PIS:Linking Importance Sampling and Attention Mechanisms for Efficient Prompt Compression
Large language models (LLMs) have achieved remarkable progress, demonstrating unprecedented capabilities across various natural …
Lizhe Chen
,
Binjia Zhou
,
Yuyao Ge 葛钰峣
,
Jiayi Chen
,
Shiguang NI
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DOI
a1: Steep Test-time Scaling Law via Environment Augmented Generation
Large Language Models (LLMs) have made remarkable breakthroughs in reasoning, yet continue to struggle with hallucinations, logical …
Lingrui Mei
,
Shenghua Liu
,
Yiwei Wang
,
Baolong Bi
,
Yuyao Ge 葛钰峣
,
Jun Wan
,
Yurong Wu
,
Xueqi Cheng
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DOI
Innate Reasoning is Not Enough : In-Context Learning Enhances Reasoning Large Language Models with Less Overthinking
TBD
Yuyao Ge 葛钰峣
,
Shenghua Liu
,
Yiwei Wang
,
Lingrui Mei
,
Lizhe Chen
,
Baolong Bi
,
Xueqi Cheng
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Cite
arXiv
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