72 citations · 136 across the 18 of their papers we have counts for
4 papers · 1 filter
Experiential Co-Learning of Software-Developing Agents
Chen Qian, Yufan Dang, Jiahao Li +9
Recent advancements in large language models (LLMs) have brought significant changes to various domains, especially through LLM-driven autonomous agents. A representative scenario…
Rational Decision-Making Agent with Internalized Utility Judgment
Yining Ye, Xin Cong, Shizuo Tian +5
Large language models (LLMs) have demonstrated remarkable advancements and have attracted significant efforts to develop LLMs into agents capable of executing intricate multi-step…
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
Yujia Qin, Shihao Liang, Yining Ye +16
Despite the advancements of open-source large language models (LLMs), e.g., LLaMA, they remain significantly limited in tool-use capabilities, i.e., using external tools (APIs) to…
Exploring the Impact of Model Scaling on Parameter-Efficient Tuning
Yusheng Su, Chi-Min Chan, Jiali Cheng +9
Parameter-efficient tuning (PET) methods can effectively drive extremely large pre-trained language models (PLMs) by training only minimal parameters. Different PET methods utilize…