1 citations · 2 across the 11 of their papers we have counts for
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cs.AI2024★ 1 cited
ReAct Meets ActRe: When Language Agents Enjoy Training Data Autonomy
Zonghan Yang, Peng Li, Ming Yan +3
Language agents have demonstrated autonomous decision-making abilities by reasoning with foundation models. Recently, efforts have been made to train language agents for performanc…
cs.IR2024★ 1 cited
ToolRerank: Adaptive and Hierarchy-Aware Reranking for Tool Retrieval
Yuanhang Zheng, Peng Li, Wei Liu +3
Tool learning aims to extend the capabilities of large language models (LLMs) with external tools. A major challenge in tool learning is how to support a large number of tools, inc…
cs.AI2024
Budget-Constrained Tool Learning with Planning
Yuanhang Zheng, Peng Li, Ming Yan +3
Despite intensive efforts devoted to tool learning, the problem of budget-constrained tool learning, which focuses on resolving user queries within a specific budget constraint, ha…