Who cites Jing Xiao
- A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
- Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
- What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction TuningarXiv:2312.15685Wei Liu, Weihao Zeng, Keqing He, et al.2023 · 178 citations
- A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
- A Comprehensive Survey on Long Context Language ModelingarXiv:2503.17407Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.2025 · 64 citations
- One-Shot Learning as Instruction Data Prospector for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yunshui Li, Binyuan Hui, Xiaobo Xia, et al.2024 · 61 citations
- Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-TuningarXiv:2402.00530Ming Li, Yong Zhang, Shwai He, et al.2024 · 60 citations
- Intern-S1: A Scientific Multimodal Foundation ModelarXiv:2508.15763Lei Bai, Zhongrui Cai, Yuhang Cao, et al.2025 · 19 citations
- What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient PerspectiveAnnual Meeting of the Association for Computational Linguistics (ACL)Ming Li, Yanhong Li, Tianyi Zhou2025 · 15 citations
- A Survey on Efficient Large Language Model Training: From Data-centric PerspectivesAnnual Meeting of the Association for Computational Linguistics (ACL)Junyu Luo, Bohan Wu, Xiao Luo, et al.2025 · 14 citations
- Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes OnarXiv:2407.08348Liang Zeng, Liangjun Zhong, Liang Zhao, et al.2024 · 14 citations
- Pangu Embedded: An Efficient Dual-system LLM Reasoner with MetacognitionarXiv:2505.22375Hanting Chen, Yasheng Wang, Kai Han, et al.2025 · 13 citations
- QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement LearningarXiv:2505.17667Fanqi Wan, Weizhou Shen, Shengyi Liao, et al.2025 · 13 citations
- Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data FilteringAnnual Meeting of the Association for Computational Linguistics (ACL)Shuzheng Si, Haozhe Zhao, Gang Chen, et al.2025 · 11 citations
- MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction FusionAnnual Meeting of the Association for Computational Linguistics (ACL)Qizhi Pei, Lijun Wu, Zhuoshi Pan, et al.2025 · 10 citations
- HS-STaR: Hierarchical Sampling for Self-Taught Reasoners via Difficulty Estimation and Budget ReallocationConference on Empirical Methods in Natural Language Processing (EMNLP)Feng Xiong, Hongling Xu, Yifei Wang, et al.2025 · 9 citations
- Understanding the Thinking Process of Reasoning Models: A Perspective from Schoenfeld's Episode TheoryConference on Empirical Methods in Natural Language Processing (EMNLP)Ming Li, Nan Zhang, Chenrui Fan, et al.2025 · 6 citations
- 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
- GATEAU: Selecting Influential Samples for Long Context AlignmentConference on Empirical Methods in Natural Language Processing (EMNLP)Shuzheng Si, Haozhe Zhao, Gang Chen, et al.2025 · 5 citations
- Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Erxin Yu, Jing Li, Ming Liao, et al.2025 · 5 citations
- Baichuan Alignment Technical ReportarXiv:2410.14940Mingan Lin, Fan Yang, Yanjun Shen, et al.2024 · 5 citations
- Select2Reason: Efficient Instruction-Tuning Data Selection for Long-CoT ReasoningFindings of the Association for Computational LinguisticsCehao Yang, Xueyuan Lin, Xiaojun Wu, et al.2026 · 4 citations
- Less is More: Selective Reflection for Compatible and Efficient Knowledge Distillation in Large Language ModelsarXiv:2508.06135Lingyuan Liu, Mengxiang Zhang2025 · 4 citations
- T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and PlaygroundConference of the European Chapter of the Association for Computational Linguistics (EACL)Dmitrii Stoianov, Danil Taranets, Olga Tsymboi, et al.2026 · 2 citations
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