Yugo Murawaki

Confidence-aware pseudo-label selection and verifier training for semi-supervised LLM reasoning with minimal labels

An adaptive threshold selection policy that chooses thresholds on validation data using pseudo-label precision and sample count is introduced and is combined with confidence-aware verifier training to support confidence-based selection of pseudo-labeled subsets.