Multiagent Finetuning: A Conversation with Researcher Yilun Du

We’re excited to be joined by Google DeepMind Senior Research Scientist Yilun Du to talk about his latest paper Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains. This paper introduces a multiagent finetuning framework that enhances the performance and diversity of language models by employing a society of agents with distinct roles, improving feedback mechanisms and overall output quality.

The method enables autonomous self-improvement through iterative finetuning, achieving significant performance gains across various reasoning tasks. It is versatile, applicable to both open-source and proprietary LLMs, and can integrate with human-feedback-based methods like RLHF or DPO, paving the way for future advancements in language model development.

Read the paper: https://arxiv.org/abs/2501.05707

Видео Multiagent Finetuning: A Conversation with Researcher Yilun Du канала Arize AI