5 citations · 14 across the 14 of their papers we have counts for
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cs.CL2024
LLMs-as-Instructors: Learning from Errors Toward Automating Model Improvement
Jiahao Ying, Mingbao Lin, Yixin Cao +5
This paper introduces the innovative "LLMs-as-Instructors" framework, which leverages the advanced Large Language Models (LLMs) to autonomously enhance the training of smaller targ…
cs.CL2024
UIO-LLMs: Unbiased Incremental Optimization for Long-Context LLMs
Wenhao Li, Mingbao Lin, Yunshan Zhong +2
Managing long texts is challenging for large language models (LLMs) due to limited context window sizes. This study introduces UIO-LLMs, an unbiased incremental optimization approa…
cs.CL2023★ 5 cited
MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation
Junru Lu, Siyu An, Mingbao Lin +5
We propose MemoChat, a pipeline for refining instructions that enables large language models (LLMs) to effectively employ self-composed memos for maintaining consistent long-range…