---
title: "Who cites What are the Essential Factors in — 13 citing papers"
description: "13 papers of the Elamur Research library cite «What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction…"
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [What are the Essential Factors in Crafting…](https://md.research.elamur.ai/free/en/papers/chen-2025-what-are-essential-factors-crafting/) / cited by

# 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»](https://md.research.elamur.ai/free/en/papers/chen-2025-what-are-essential-factors-crafting/)

1. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
2. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
3. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
4. **[MDCure: A Scalable Pipeline for Multi-Document Instruction-Following](https://md.research.elamur.ai/free/en/papers/liu-2025-mdcure-scalable-pipeline-multi-document/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gabrielle Kaili-May Liu, Bowen Shi, Avi Caciularu, et al.*2025 · 11 citations*
5. **[Data Foundations of Long-Context Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/sun-2026-data-foundations-long-context-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zechen Sun, Yuyang Sun, Zhaochen Su, et al.*2026*
6. **[HopWeaver: Cross-Document Synthesis of High-Quality and Authentic Multi-Hop Questions](https://md.research.elamur.ai/free/en/papers/shen-2026-hopweaver-cross-document-synthesis-high/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyu Shen, Jiyuan Liu, Yunhe Pang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/chen-2025-what-are-essential-factors-crafting/) — What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices