ExpHarness: Model-Agnostic Experience Learning through a Trainable Harness
ExpHarness introduces a trainable harness that allows Large Language Models (LLMs) to learn from experience without retraining the LLM itself. It attempts to solve this by creating a framework where an external, structured memory stores past interactions. The result is a system that uses this memory and an adaptive retrieval mechanism to improve the performance of frozen LLM executors through experience reuse.