Andrey Sakhovskiy

The presence of factual hallucinations in large language model (LLM) generations drives the development of retrieval-augmented factuality evaluation tools. However, existing implementations suffer from slow inference, outdated knowledge bases, and the use of paid search and LLM APIs, which hinder...

Large language model (LLM) agents improve task performance by decomposing problems into role-specialized behaviors. However, their practical deployment is often limited by the computational cost and instability associated with the on-the-fly agent design for each user request. To address this, we...