🔗 Who cites «QuRating: Selecting High-Quality Data for Training Language Models»

68 papers of our library cite it (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · ← back to «QuRating: Selecting High-Quality Data for Training Language Models»

1. A Survey on Large Language Models for Code GenerationACM Transactions on Software Engineering and MethodologyJuyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
2. InternLM2 Technical ReportarXiv:2403.17297Zheng Cai, Maosong Cao, Haojiong Chen, et al.2024 · 301 citations
3. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
4. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
5. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
6. How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 89 citations
7. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
8. RegMix: Data Mixture as Regression for Language Model Pre-trainingarXiv:2407.01492Qian Liu, Xiaosen Zheng, Niklas Muennighoff, et al.2024 · 57 citations
9. What is the Role of Small Models in the LLM Era: A SurveyComputational LinguisticsLihu Chen, Gael Varoquaux2024 · 23 citations
10. Unearthing Large Scale Domain-Specific Knowledge from Public CorporaarXiv:2401.14624Zhaoye Fei, Yunfan Shao, Linyang Li, et al.2024 · 10 citations
11. Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy ParadigmConference on Empirical Methods in Natural Language Processing (EMNLP)Zhuo Li, Yuhao Du, Xiaoqi Jiao, et al.2025 · 5 citations
12. Long-Chain Reasoning Distillation via Adaptive Prefix AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenghao Liu, Zhuoyang Wu, Xinze Li, et al.2026 · 3 citations
13. SynthRL: Scaling Visual Reasoning with Verifiable Data SynthesisFindings of the Association for Computational LinguisticsZijian Wu, Jinjie Ni, Xiangyan Liu, et al.2026 · 3 citations
14. Enhancing Long-Chain Reasoning Distillation through Error-Aware Self-ReflectionFindings of the Association for Computational LinguisticsZhuoyang Wu, Xinze Li, Zhenghao Liu, et al.2026 · 1 citation
15. From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for TibetanAnnual Meeting of the Association for Computational Linguistics (ACL)Lei Yang, Leiyu Pan, Bojian Xiong, et al.2026 · 1 citation
16. Data-Efficient Adaptation to Contextual Shifts in LLM-based Conversational RecommendationFindings of the Association for Computational LinguisticsHyeongjun Yang, Donghyun Kim, Seokju Hwang, et al.2026
17. Detecting Non-Membership in LLM Training Data via Rank CorrelationsConference of the European Chapter of the Association for Computational Linguistics (EACL)Pranav Shetty, Mirazul Haque, Zhiqiang Ma, et al.2026
18. How Does "English (US)" Become the Default? Triangulating Structural Bias Towards American English Across the LLM PipelinearXiv:2604.04204Mir Tafseer Nayeem, Davood Rafiei2026
19. InstructDiff: Domain-Adaptive Data Selection via Contrastive Entropy for Efficient LLM Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Junyou Su, He Zhu, Xiao Luo, et al.2026
20. Large-Scale Diverse Synthesis for Mid-TrainingFindings of the Association for Computational LinguisticsXuemiao Zhang, Chengying Tu, Can Ren, et al.2026
21. LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge PointsAnnual Meeting of the Association for Computational Linguistics (ACL)Xuemiao Zhang, Can Ren, Chengying Tu, et al.2026
22. Rethinking Data Mixing from the Perspective of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuanjian Xu, Tianze Sun, Changwei Xu, et al.2026

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

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