AIBullisharXiv – CS AI · Apr 157/10
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Transferable Expertise for Autonomous Agents via Real-World Case-Based Learning
Researchers propose a case-based learning framework enabling LLM-based autonomous agents to extract and reuse knowledge from past tasks, improving performance on complex real-world problems. The method outperforms traditional zero-shot, few-shot, and prompt-based baselines across six task categories, with gains increasing as task complexity rises.