HERA: Harness-Environment Co-Evolution for Reliable Agentic Abstention
Large language model (LLM) agents are increasingly capable of acting in complex tool-use environments, yet they often fail to recognize when tasks are infeasible and no valid solution exists. Recent work has formalized this reliability gap as the problem of agentic abstention, and existing approaches typically optimize...
Hang Luo, Bing-Bing Wen, Guang Yang et al.
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