🔗 Who cites «HelpSteer2-Preference: Complementing Ratings with Preferences»

53 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · ← back to «HelpSteer2-Preference: Complementing Ratings with Preferences»

1. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
2. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 195 citations
3. LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context MultitasksarXiv:2412.15204Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.2024 · 135 citations
4. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
5. Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI SynergyarXiv:2507.01352Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.2025 · 48 citations
6. AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward ModelingFindings of the Association for Computational LinguisticsZihan Liu, Yang Chen, Mohammad Shoeybi, et al.2025 · 37 citations
7. Checklists Are Better Than Reward Models For Aligning Language ModelsConference on Neural Information Processing Systems (NeurIPS)Vijay Viswanathan, Yanchao Sun, Shuang Ma, et al.2025 · 37 citations
8. U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMsarXiv:2412.03205Konstantin Chernyshev, Vitaliy Polshkov, Ekaterina Artemova, et al.2024 · 13 citations
9. TRAIL: Trace Reasoning and Agentic Issue LocalizationarXiv:2505.08638Darshan Deshpande, Varun Gangal, Hersh Mehta, et al.2025 · 12 citations
10. Puzzle: Distillation-Based NAS for Inference-Optimized LLMsarXiv:2411.19146Akhiad Bercovich, Tomer Ronen, Talor Abramovich, et al.2024 · 10 citations
11. Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal UncertaintyFindings of the Association for Computational LinguisticsChao Xue, Yao Wang, Mengqiao Liu, et al.2026 · 8 citations
12. Outcome Accuracy is Not Enough: Aligning the Reasoning Process of Reward ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Binghai Wang, Yantao Liu, Yuxuan Liu, et al.2026 · 3 citations
13. Preference Learning Unlocks LLMs' Psycho-Counseling SkillsFindings of the Association for Computational LinguisticsMian Zhang, Shaun M. Eack, Zhiyu Chen2026 · 2 citations
14. Automated Creativity Evaluation of Language Models Across Open-Ended TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Tan Min Sen, Zachary Choy Kit Chun, Syed Ali Redha Alsagoff, et al.2026 · 1 citation
15. Debiasing Reward Models via Causally Motivated Inference-Time InterventionAnnual Meeting of the Association for Computational Linguistics (ACL)Kazutoshi Shinoda, Kosuke Nishida, Kyosuke Nishida2026
16. Self-Guided Alignment: Adaptive Preference Sensing for Multi-Objective GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Ning Wang, Zhanyang Liu, Taotao Zhou, et al.2026
17. SPARTA: Evaluating Reasoning Segmentation Robustness through Black-Box Adversarial Paraphrasing in Text Autoencoder Latent SpaceConference of the European Chapter of the Association for Computational Linguistics (EACL)Viktoriia Zinkovich, Anton Antonov, Andrei Spiridonov, et al.2026
18. WildReward: Learning Reward Models from In-the-Wild Human InteractionsAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.2026

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