Sangyeon Yoon

Diagnosing and Correcting Reward Hacking in Verifiable Instruction Following

A preprint argues that verifiable instruction-following benchmarks can give full credit to answers with little substance, and that using the same verifier as a training reward induces reward hacking. It proposes CALIF, a likelihood-based bonus to preserve response quality.