pat-jj/s3
A research project training search agents using reinforcement learning with minimal data to improve RAG system efficiency.
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This repository implements an RL-based approach for training efficient search agents in RAG (Retrieval Augmented Generation) systems. The method uses verifier-based reinforcement learning to optimize search agent behavior with minimal training data. Published at EMNLP 2025, it focuses on improving both the effectiveness and efficiency of retrieval-augmented language model applications.
Frequently asked
- What is pat-jj/s3?
- A research project training search agents using reinforcement learning with minimal data to improve RAG system efficiency.
- Is s3 open source?
- Yes — pat-jj/s3 is open source, released under the Apache-2.0 license.
- What language is s3 written in?
- pat-jj/s3 is primarily written in Python.
- How popular is s3?
- pat-jj/s3 has 842 stars on GitHub.
- Where can I find s3?
- pat-jj/s3 is on GitHub at https://github.com/pat-jj/s3.