🔗 Who cites «Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision»

49 papers of our library cite it (of the 149,439 whose bibliographies we read) · 23 with a page here, the most cited first · ← back to «Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision»

1. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructarXiv:2308.09583Haipeng Luo, Qingfeng Sun, Can Xu, et al.2023 · 372 citations
2. SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the WildarXiv:2503.18892Weihao Zeng, Yuzhen Huang, Qian Liu, et al.2025 · 154 citations
3. Generative Verifiers: Reward Modeling as Next-Token PredictionarXiv:2408.15240Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.2024 · 152 citations
4. Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language ModelsarXiv:2408.00724Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.2024 · 122 citations
5. Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language ModelsarXiv:2601.18734Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.2026 · 97 citations
6. O1 Replication Journey: A Strategic Progress Report — Part 1arXiv:2410.18982Yiwei Qin, Xuefeng Li, Haoyang Zou, et al.2024 · 86 citations
7. AI Agents That MatterarXiv:2407.01502Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, et al.2024 · 55 citations
8. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
9. LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical ReasoningarXiv:2410.02884Di Zhang, Jianbo Wu, Jingdi Lei, et al.2024 · 49 citations
10. Improve Vision Language Model Chain-of-thought ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Ruohong Zhang, Bowen Zhang, Yanghao Li, et al.2025 · 42 citations
11. A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic SystemsarXiv:2504.09037Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.2025 · 39 citations
12. MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Justin Chen, Archiki Prasad, Swarnadeep Saha, et al.2025 · 20 citations
13. A Survey of Post-Training Scaling in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hanyu Lai, Xiao Liu, Junjie Gao, et al.2025 · 18 citations
14. R-PRM: Reasoning-Driven Process Reward ModelingConference on Empirical Methods in Natural Language Processing (EMNLP)Shuaijie She, Junxiao Liu, Yifeng Liu, et al.2025 · 18 citations
15. Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language ModelsarXiv:2412.02980Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.2024 · 17 citations
16. Can Large Reasoning Models Self-Train?arXiv:2505.21444Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.2025 · 16 citations
17. Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive SearcharXiv:2502.02508Maohao Shen, Guangtao Zeng, Zhenting Qi, et al.2025 · 13 citations
18. When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM ReasoningarXiv:2504.01005Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.2025 · 12 citations
19. AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and TreefinementarXiv:2412.06176Pranjal Aggarwal, Bryan Parno, Sean Welleck2024 · 11 citations
20. Progressive Multimodal Reasoning via Active RetrievalAnnual Meeting of the Association for Computational Linguistics (ACL)Guanting Dong, Chenghao Zhang, Mengjie Deng, et al.2025 · 10 citations
21. From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language ModelsFindings of the Association for Computational LinguisticsJiaxin Zhang, Wendi Cui, Zhuohang Li, et al.2026 · 1 citation
22. Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Raffaele Pisano, Roberto Navigli2026 · 1 citation
23. GALA: Geometric Data Selection with Strategic Prospecting for Large Language Model Self-trainingFindings of the Association for Computational LinguisticsZhongwei Xie, Ruihao Liao, Zimo Wang, et al.2026

26 more papers of our library cite it; they have no page here yet.

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