Reward models are metrics in disguise

Different labels, same pitfalls.

This position paper argues that reward models (for RL-based LLM training) and evaluation metrics face overlapping challenges—spurious correlations, reward hacking, data quality, and meta-evaluation. In some tasks, metrics even outperform reward models.

Why it matters: Aligning these research communities could improve preference elicitation, robustness to spurious signals, and calibration-aware evaluation.

It’s two sides of the same coin; flip it wisely. 🪙🧠🔍

Explore the survey and proposed research directions—then share where unifying efforts could help most.

Paper: http://arxiv.org/abs/2510.03231v1

Register: https://www.AiFeta.com

Paper: http://arxiv.org/abs/2510.03231v1

Register: https://www.AiFeta.com

#LLM #RLHF #Evaluation #AIAlignment #Metrics #RewardModels #MLResearch