% Key papers for Process reward models (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2021_measuring_61421,
  title = {{Measuring Mathematical Problem Solving With the MATH Dataset}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://openreview.net/forum?id=7Bywt2mQsCe},
}

@inproceedings{neurips2024_rest_70786,
  title = {{ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96343},
}

@inproceedings{iclr2025_generative_81265,
  title = {{Generative Verifiers: Reward Modeling as Next-Token Prediction}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30506},
}

@inproceedings{aaai2026_genprm_108445,
  title = {{GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40797},
}

@inproceedings{icml2025_free_46282,
  title = {{Free Process Rewards without Process Labels}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46278},
}

@inproceedings{neurips2025_adastar_75878,
  title = {{AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=D6PwC6Xogv},
}

@inproceedings{neurips2025_reward_77551,
  title = {{Reward Reasoning Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=V8Kbz7l2cr},
}

@inproceedings{neurips2025_antidistillation_77622,
  title = {{Antidistillation Sampling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Vo2UHqMu8t},
}

@inproceedings{neurips2025_reasonflux_78471,
  title = {{ReasonFlux-PRM: Trajectory-Aware PRMs for Long Chain-of-Thought Reasoning in LLMs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=f3sZjkQbv2},
}

@inproceedings{iclr2026_tattoo_89500,
  title = {{TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular Reasoning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=zc1ezBrr5m},
}

@inproceedings{icml2025_adaptivestep_47543,
  title = {{AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45053},
}

@inproceedings{icml2025_discriminative_47824,
  title = {{Discriminative Policy Optimization for Token-Level Reward Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44776},
}

@inproceedings{icml2025_versaprm_48393,
  title = {{VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44223},
}

@inproceedings{icml2026_adversarial_49603,
  title = {{Adversarial Training for Process Reward Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=43Hwj59jZg},
}

@inproceedings{icml2026_seccodeprm_51986,
  title = {{SecCodePRM: A Process Reward Model for Code Security}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Rg73g42KBW},
}

@inproceedings{icml2026_convex_54352,
  title = {{Convex Dataset Valuation for Post-Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=oAAL0wZSMF},
}

@inproceedings{neurips2025_unlocking_75526,
  title = {{Unlocking Multimodal Mathematical Reasoning via Process Reward Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=96I8PGPALv},
}

@inproceedings{neurips2025_treasure_76705,
  title = {{Treasure Hunt: Real-time Targeting of the Long Tail using Training-Time Markers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=MDUt8t5b34},
}

@inproceedings{neurips2025_improving_77083,
  title = {{Improving Generalization of Neural Combinatorial Optimization for Vehicle Routing Problems via Test-Time Projection Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=QPJjiNCRq1},
}

@inproceedings{neurips2025_dreamprm_77995,
  title = {{DreamPRM: Domain-reweighted Process Reward Model for Multimodal Reasoning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=ZyiBk1ZinG},
}

@inproceedings{neurips2025_know_78757,
  title = {{Know What You Don't Know: Uncertainty Calibration of Process Reward Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=hzMkfIrdDT},
}