Cleaning data and aligning the reward function for RLVR takes expertise and effort upfront, but the result is a model that's state-of-the-art on a complex task.
Guest post by researchers at UIUC and Bridgewater, in collaboration with our team.
https://t.co/1UHTXFcZnW https://t.co/ezB1anl4KC
Fixing labels and aligning the verifier, not adding scaffolding or a better optimizer, is what carried a text-to-SQL model past the human baseline on a task where LLMs had lagged.
