Latent Agents: A Post-Training Procedure for Internalized Multi-Agent Debate

AI & Machine Learning > MLOps & ML Systems(arxiv.org)view on HackerNews

multi-agent debatelarge language modelsMLOpsinternalizationdynamic reward schedulinglength clipping

Author: PaulHoule

Date: 6/4/2026

Article Summary:

This paper presents a post-training procedure for internalized multi-agent debate in large language models (LLMs), which improves reasoning and reduces computational inefficiency.