PieceHint strategically scores and injects critical reasoning hints in RL training to let a 1.5B model match 32B baselines on math benchmarks while preserving pass@k diversity.
StepHint prepends the first 25% of ground- truth solution steps as positional prefix hints—the best-performing variant of StepHint as identified in our ablation studies (Table 2)
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Placing Puzzle Pieces Where They Matter: A Question Augmentation Framework for Reinforcement Learning
PieceHint strategically scores and injects critical reasoning hints in RL training to let a 1.5B model match 32B baselines on math benchmarks while preserving pass@k diversity.