Presents verifiable counterfactual process supervision that generates annotated trajectories via template-aware error injection on symbolic chains, improving Best-of-8 reranking on logical reasoning benchmarks with preliminary math transfer.
InProceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 22017–22031, Miami, Florida, USA
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Verifiable Counterfactual Supervision for Process Reward Models
Presents verifiable counterfactual process supervision that generates annotated trajectories via template-aware error injection on symbolic chains, improving Best-of-8 reranking on logical reasoning benchmarks with preliminary math transfer.