The NeurIPS 2025 conference has announced a new competition focused on evaluating language models early in their training process. The E2LM (Early Training Evaluation of Language Models) Competition aims to advance techniques for predicting model performance before full training completes.
Participants will be tasked with developing methods to assess language model quality using only early training checkpoints. The competition seeks to address the high computational cost of training large models by enabling early identification of promising architectures and data configurations.
Key details include:
- Goal: Predict final model performance from early training stages.
- Focus: Evaluation metrics and methods for LMs.
- Timeline: Detailed schedule to be announced on the official NeurIPS competitions page.
The challenge encourages innovation in efficient evaluation protocols, potentially reducing resource usage in AI development.