🔗 Who cites «OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment»

23 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · ← back to «OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment»

1. AttnPO: Attention-Guided Process Supervision for Efficient ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Shuaiyi Nie, Dingsiyu, Wenyuan Zhang, et al.2026 · 18 citations
2. RubricHub: A Comprehensive and Highly Discriminative Rubric Dataset via Automated Coarse-to-Fine GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Sunzhu Li, Jiale Zhao, Huimin Ren, et al.2026 · 9 citations
3. RubricBench: Aligning Model-Generated Rubrics with Human StandardsAnnual Meeting of the Association for Computational Linguistics (ACL)Junyi Zhou, Qiyuan Zhang, Yufei Wang, et al.2026 · 3 citations
4. IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Bosi Wen, Yilin Niu, Cunxiang Wang, et al.2026 · 1 citation
5. P-Check: Advancing Personalized Reward Model via Learning to Generate Dynamic ChecklistAnnual Meeting of the Association for Computational Linguistics (ACL)Kwangwook Seo, Dongha Lee2026 · 1 citation
6. SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data UtilityAnnual Meeting of the Association for Computational Linguistics (ACL)Xuyang Zhi, Peilun Zhou, Chengqiang Lu, et al.2026 · 1 citation
7. Alignment Tuning for Large Language Models: A Data-Centric Lens on Alignment Data PipelinesFindings of the Association for Computational LinguisticsHwanjun Song2026
8. Reward Modeling for Scientific Writing EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Furkan Şahinuç, Subhabrata Dutta, Iryna Gurevych2026
9. RiT: Rubrics-in-Thinking Reinforcement Learning for Improved Reasoning in Large Language ModelsFindings of the Association for Computational LinguisticsXiaobin Tian, Shuai Yuan, Muyun Ding, et al.2026

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

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