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cs.AI2026
Exploring Agentic Tool-Calling Decisions via Uncertainty-Aligned Reinforcement Learning
Yijin Zhou, Linqian Zeng, Xiaoya Lu +4
Large language model (LLM)-based agents often make suboptimal tool-use decisions, including unsupported tool invocation and hallucinated direct responses, which may accumulate erro…
cs.AI2026
BEAM: Bi-level Memory-adaptive Algorithmic Evolution for LLM-Powered Heuristic Design
Chuyang Xiang, Yichen Wei, Jiale Ma +2
Large Language Model-based Hyper Heuristic (LHH) has recently emerged as an efficient way for automatic heuristic design. However, most existing LHHs just perform well in optimizin…