2 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Towards Automatic Continual Learning: A Self-Adaptive Framework for Continual Instruction Tuning
Peiyi Lin, Fukai Zhang, Kai Niu +1
Continual instruction tuning enables large language models (LLMs) to learn incrementally while retaining past knowledge, whereas existing methods primarily focus on how to retain o…
Collab-Overcooked: Benchmarking and Evaluating Large Language Models as Collaborative Agents
Haochen Sun, Shuwen Zhang, Lujie Niu +6
Large Language Models (LLMs) based agent systems have made great strides in real-world applications beyond traditional NLP tasks. This paper proposes a new LLM-based Multi-Agent Sy…
Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach
Param Kulkarni, Yingchi Liu, Hao-Ming Fu +8
Achieving a delicate balance between fostering trust in law enforcement and protecting the rights of both officers and civilians continues to emerge as a pressing research and prod…
StringLLM: Understanding the String Processing Capability of Large Language Models
Xilong Wang, Hao Fu, Jindong Wang +1
String processing, which mainly involves the analysis and manipulation of strings, is a fundamental component of modern computing. Despite the significant advancements of large lan…