代理工具
Meta Lets a Recommender-Systems Research Agent Take Over Multi-Day GPU Experiments Across Servers, Cutting Operational Fixes to 0.5 per Run
Auto-RecSys links research ideas, distributed training, failure recovery, and results analysis in a dual-loop system that persists across sessions. In 31 internal experiments, operational fixes fell from 4.0 to 0.5 per run, but Meta has not yet shown that the agent’s proposed model changes can consistently improve recommendation quality.