Who cites «In-context Pretraining: Language Modeling Beyond Document Boundaries»
- A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,231 citations
- Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextarXiv:2403.05530Gemini Team, Petko Georgiev, Ving Ian Lei, et al.2024 · 1,589 citations
- A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
- Hallucination is Inevitable: An Innate Limitation of Large Language ModelsarXiv:2401.11817Ziwei Xu, Sanjay Jain, Mohan Kankanhalli2024 · 312 citations
- MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
- Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 182 citations
- RAFT: Adapting Language Model to Domain Specific RAGarXiv:2403.10131Tianjun Zhang, Shishir G. Patil, Naman Jain, et al.2024 · 137 citations
- OpenCodeInterpreter: Integrating Code Generation with Execution and RefinementFindings of the Association for Computational LinguisticsTianyu Zheng, Ge Zhang, Tianhao Shen, et al.2024 · 129 citations
- Make Your LLM Fully Utilize the ContextConference on Neural Information Processing Systems (NeurIPS)Shengnan An, Zexiong Ma, Zeqi Lin, et al.2024 · 97 citations
- A Comprehensive Survey on Long Context Language ModelingarXiv:2503.17407Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.2025 · 64 citations
- Instruction Pre-Training: Language Models are Supervised Multitask LearnersConference on Empirical Methods in Natural Language Processing (EMNLP)Daixuan Cheng, Yuxian Gu, Shaohan Huang, et al.2024 · 59 citations
- Dataset Decomposition: Faster LLM Training with Variable Sequence Length CurriculumConference on Neural Information Processing Systems (NeurIPS)Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, et al.2024 · 16 citations
- What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best PracticesAnnual Meeting of the Association for Computational Linguistics (ACL)Zhi Chen, Qiguang Chen, Libo Qin, et al.2025 · 15 citations
- MDCure: A Scalable Pipeline for Multi-Document Instruction-FollowingAnnual Meeting of the Association for Computational Linguistics (ACL)Gabrielle Kaili-May Liu, Bowen Shi, Avi Caciularu, et al.2025 · 11 citations
- Yi-Lightning Technical ReportarXiv:2412.01253Alan Wake, Bei Chen, C.X. Lv, et al.2024 · 11 citations
- Data Foundations of Long-Context Language Models: A SurveyTransactions of the Association for Computational Linguistics (TACL)Zechen Sun, Yuyang Sun, Zhaochen Su, et al.2026
This page in Markdown → https://md.research.elamur.ai/free/en/papers/shi-2023-context-pretraining-language-modeling-document/cited-by/