Deep Learning

Reactive Optimizers

Xingjian Bai, Jia-Hao Liang, Jayden Teoh and Vincent Sitzmann put an LLM agent inside the optimizer: it watches training dynamics and rewrites the optimizer's source code mid-run. Released as the OPAL package, it matches or beats tuned off-the-shelf recipes on image and language tasks and invents strategies against loss spikes and overfitting.

Research · Machine Learning · AI Agents · Optimization · Deep Learning