Baidu framework makes RAG more traceable
A Baidu post published on July 30, 2024 describes a framework that evaluates retrieved documents, selects evidence, and analyzes reasoning paths before answering.
Source: Framework de self-reasoning da Baidu para RAG (x.com). Text prepared with AI from this source.
What happened and what to do
In a post published on July 30, 2024, Baidu describes a self-reasoning framework for RAG. A language model evaluates the relevance of retrieved documents, selects and cites passages as evidence, and analyzes reasoning paths before producing an answer. According to the post, the method achieves performance comparable to GPT-4 using 2,000 training examples generated by that model.
A company can implement explicit relevance evaluation and evidence selection in its RAG flow, recording the sources that support each answer. A project could include quality tests, citation monitoring, and analysis of cases where retrieval or the answer fails.
How the consultancy can help
Wendelmaques can diagnose a RAG flow and its traceability requirements, define an implementation for relevance evaluation, evidence, and monitoring, and propose its operation on the company’s infrastructure.
Next step
Send a short description of your RAG case to receive a proposal scoped for diagnosis and implementation.
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