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A Survey of Context Engineering for Large Language Models
The performance of Large Language Models (LLMs) is fundamentally determined by the contextual information provided during inference. …
Lingrui Mei, Jiayu Yao, Yuyao Ge 葛钰峣, Yiwei Wang, Baolong Bi, Yujun Cai, Jiazhi Liu, Mingyu Li, Zhong-Zhi Li, Duzhen Zhang, Chenlin Zhou, Jiayi Mao, Tianze Xia, Jiafeng Guo, Shenghua Liu
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A Survey of Context Engineering for Large Language Models
Who is in the Spotlight: The Hidden Bias Undermining Multimodal Retrieval-Augmented Generation
Multimodal Retrieval-Augmented Generation (RAG) systems have become essential in knowledge-intensive and open-domain tasks. As …
Jiayu Yao, Shenghua Liu, Yiwei Wang, Lingrui Mei, Baolong Bi, Yuyao Ge 葛钰峣, Zhecheng Li, Xueqi Cheng
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Who is in the Spotlight: The Hidden Bias Undermining Multimodal Retrieval-Augmented Generation
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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PIS:Linking Importance Sampling and Attention Mechanisms for Efficient Prompt Compression
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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a1: Steep Test-time Scaling Law via Environment Augmented Generation
Innate Reasoning is Not Enough : In-Context Learning Enhances Reasoning Large Language Models with Less Overthinking
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Yuyao Ge 葛钰峣, Shenghua Liu, Yiwei Wang, Lingrui Mei, Lizhe Chen, Baolong Bi, Xueqi Cheng
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Innate Reasoning is Not Enough : In-Context Learning Enhances Reasoning Large Language Models with Less Overthinking