A case-based learning framework extracts reusable knowledge from past tasks to improve LLM agents' structured performance on complex real-world tasks, outperforming standard prompting baselines especially as task complexity grows.
ExpeL: LLM Agents Are Experiential Learners
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Transferable Expertise for Autonomous Agents via Real-World Case-Based Learning
A case-based learning framework extracts reusable knowledge from past tasks to improve LLM agents' structured performance on complex real-world tasks, outperforming standard prompting baselines especially as task complexity grows.