Introducing Celo2: Towards Learned Optimization Free Lunch We show that learned optimizers can generalize to practical tasks like GPT-3 1.3B pretraining and several out-of-distribution vision/RL tasks from limited meta-training (~4.5 GPU hours)! 🧵

New side project! assayer: A simple Python-RQ based tool to automatically monitor and evaluate ML model checkpoints offline during training.

Excited to share our recent work, AuPair, an inference-time technique that builds on the premise of in-context learning to improve LLM coding performance! arxiv.org/abs/2502.18487 🧵

AuPair: Golden Example Pairs for Code Repair

Scaling up inference-time compute has proven to be a valuable strategy in improving the performance of Large Language Models (LLMs) without fine-tuning. An important task that can benefit from additio...

arxiv.org