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cs.CL2025
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…
cs.CL2025★ 1 cited
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…
cs.CL2025
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…