TL;DR: A dataset of 35 million examples for process reward modeling has been released, enabling finer-grained reward signals for RLHF.
Summary: A dataset containing 35 million examples for process reward modeling was released. The dataset is designed to train models that provide step-by-step rewards, improving upon traditional outcome-based reward models. The specific source or creator of the dataset is not detailed.
Why it matters: This dataset allows AI builders to train more nuanced reward models for reinforcement learning, enhancing alignment and reasoning in LLMs. Consider experimenting with it to improve your own reward modeling pipelines.
Source: @tom_doerr