Small 7B reasoning models were fine-tuned on synthetic and curated QFT problems using RL and SFT, yielding performance gains, error analysis, and public release of data and traces.
Sharp: Synthesizing high-quality aligned reasoning problems for large reasoning models reinforcement learning
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VHG integrates a verifier into three-party self-play to produce valid, challenging math problems, outperforming baselines on indefinite integral and general reasoning tasks.
citing papers explorer
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Fine-Tuning Small Reasoning Models for Quantum Field Theory
Small 7B reasoning models were fine-tuned on synthetic and curated QFT problems using RL and SFT, yielding performance gains, error analysis, and public release of data and traces.
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Verifier-Backed Hard Problem Generation for Mathematical Reasoning
VHG integrates a verifier into three-party self-play to produce valid, challenging math problems, outperforming baselines on indefinite integral and general reasoning tasks.