A policy-agnostic metric and controllable 2D grid environments with task DAGs enable measurement of exploration and exploitation errors in language model agents from observed actions.
Expanding LLM agent boundaries with strategy-guided exploration.arXiv preprint arXiv:2603.02045
3 Pith papers cite this work. Polarity classification is still indexing.
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Mastermind's dual-loop planner learns transferable strategies via SFT and milestone GRPO, raising GPT-5.5 executor pass rate on 200 held-out CyberGym tasks from 60% to 84.5%.
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Exploration and Exploitation Errors Are Measurable for Language Model Agents
A policy-agnostic metric and controllable 2D grid environments with task DAGs enable measurement of exploration and exploitation errors in language model agents from observed actions.
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Mastermind: Strategy-grounded Learning for Repository-Scale Vulnerability Reproduction
Mastermind's dual-loop planner learns transferable strategies via SFT and milestone GRPO, raising GPT-5.5 executor pass rate on 200 held-out CyberGym tasks from 60% to 84.5%.
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