🔗 Who cites «What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices»

13 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices»

1. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
2. A Comprehensive Survey on Long Context Language ModelingarXiv:2503.17407Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.2025 · 64 citations
3. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
4. 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
5. 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
6. HopWeaver: Cross-Document Synthesis of High-Quality and Authentic Multi-Hop QuestionsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyu Shen, Jiyuan Liu, Yunhe Pang, et al.2026

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

This page in Markdown → https://md.research.elamur.ai/free/en/papers/chen-2025-what-are-essential-factors-crafting/cited-by/