Meta researchers open the LLM black box to repair flawed AI reasoning

This post was originally published by [email protected] (Ben Dickson) on Venture Beat.

Researchers at Meta FAIR and the University of Edinburgh have developed a new technique that can predict the correctness of a large language model’s (LLM) reasoning and even intervene to fix its mistakes. Called Circuit-based Reasoning Verification (CRV), the method looks inside an LLM to monitor its internal “reasoning circuits” and detect signs of computational errors as the model solves a problem.

Their findings show that CRV can detect reasoning errors in LLMs with high accuracy by building and observing a computational graph from the model’s internal activations. In a key breakthrough, the researchers also demonstrated they can use this deep