2 citations · 4 across the 12 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
cs.CL2025
ATLaS: Agent Tuning via Learning Critical Steps
Zhixun Chen, Ming Li, Yuxuan Huang +3
Large Language Model (LLM) agents have demonstrated remarkable generalization capabilities across multi-domain tasks. Existing agent tuning approaches typically employ supervised f…
cs.CL2025
Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones?
Yudi Zhang, Lu Wang, Meng Fang +8
Distilling large language models (LLMs) typically involves transferring the teacher model's responses through supervised fine-tuning (SFT). However, this approach neglects the pote…
cs.CL2023★ 1 cited
Cooperation on the Fly: Exploring Language Agents for Ad Hoc Teamwork in the Avalon Game
Zijing Shi, Meng Fang, Shunfeng Zheng +3
Multi-agent collaboration with Large Language Models (LLMs) demonstrates proficiency in basic tasks, yet its efficiency in more complex scenarios remains unexplored. In gaming envi…