27 citations · 38 across the 10 of their papers we have counts for
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cs.AI2024
Unveiling and Consulting Core Experts in Retrieval-Augmented MoE-based LLMs
Xin Zhou, Ping Nie, Yiwen Guo +7
Retrieval-Augmented Generation (RAG) significantly improved the ability of Large Language Models (LLMs) to solve knowledge-intensive tasks. While existing research seeks to enhance…
cs.CL2024★ 1 cited
LongHeads: Multi-Head Attention is Secretly a Long Context Processor
Yi Lu, Xin Zhou, Wei He +5
Large language models (LLMs) have achieved impressive performance in numerous domains but often struggle to process lengthy inputs effectively and efficiently due to limited length…
cs.CL2024★ 1 cited
Are Large Language Models Good Prompt Optimizers?
Ruotian Ma, Xiaolei Wang, Xin Zhou +5
LLM-based Automatic Prompt Optimization, which typically utilizes LLMs as Prompt Optimizers to self-reflect and refine prompts, has shown promising performance in recent studies. D…