arxiv
PublishedApril 8, 2026 at 4:00 AM
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Hierarchical Reinforcement Learning with Augmented Step-Level Transitions for LLM Agents
Publisher summary· verbatim
arXiv:2604.05808v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong capabilities in complex interactive decision-making tasks. However, existing LLM agents typically rely on increasingly long interaction histories, resulting in high computational cost and limit
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Originally published on arxiv ↗