Adaptive scheduling of penalties over training time plus confidence-based weighting of mistakes improves LLM performance on math reasoning benchmarks compared to fixed-penalty negative reinforcement.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
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Adaptive Negative Reinforcement for LLM Reasoning:Dynamically Balancing Correction and Diversity in RLVR
Adaptive scheduling of penalties over training time plus confidence-based weighting of mistakes improves LLM performance on math reasoning benchmarks compared to fixed-penalty negative reinforcement.