A leaderboard-driven LLM-agent framework improved product-to-catalog matching coverage from a 33.3% baseline to 47.8-57.4% with one agent and up to 69.4% with five parallel agents, while parallel agents explored qualitatively different methods.
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Continuous Improvement and Parallel Autonomous Exploration: An LLM-Agent Framework for Searching Large Solution Spaces
A leaderboard-driven LLM-agent framework improved product-to-catalog matching coverage from a 33.3% baseline to 47.8-57.4% with one agent and up to 69.4% with five parallel agents, while parallel agents explored qualitatively different methods.