97 citations · 101 across the 11 of their papers we have counts for
7 papers · 2 filters
AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning
Hao Sun, Jiayi Wu, Hengyi Cai +6
Recent advancements in large language models (LLMs) have been remarkable. Users face a choice between using cloud-based LLMs for generation quality and deploying local-based LLMs f…
Retrieved In-Context Principles from Previous Mistakes
Hao Sun, Yong Jiang, Bo Wang +4
In-context learning (ICL) has been instrumental in adapting Large Language Models (LLMs) to downstream tasks using correct input-output examples. Recent advances have attempted to…
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…
A + B: A General Generator-Reader Framework for Optimizing LLMs to Unleash Synergy Potential
Wei Tang, Yixin Cao, Jiahao Ying +4
Retrieval-Augmented Generation (RAG) is an effective solution to supplement necessary knowledge to large language models (LLMs). Targeting its bottleneck of retriever performance,…
EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain
Yi-Fan Lu, Xian-Ling Mao, Bo Wang +2
It is crucial to understand a specific domain by events. Extensive event extraction research has been conducted in many domains such as news, finance, and biology. However, event e…
QRMeM: Unleash the Length Limitation through Question then Reflection Memory Mechanism
Bo Wang, Heyan Huang, Yixin Cao +3
While large language models (LLMs) have made notable advancements in natural language processing, they continue to struggle with processing extensive text. Memory mechanism offers…