---
title: "Who cites RAGEval: Scenario Specific RAG — 17 citing papers"
description: "17 papers of the Elamur Research library cite «RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/zhu-2025-rageval-scenario-specific-rag-evaluation/cited-by/"
---
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# Who cites «RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework»

17 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 «RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework»](https://md.research.elamur.ai/free/en/papers/zhu-2025-rageval-scenario-specific-rag-evaluation/)

1. **[OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-opengenalign-preference-dataset-benchmark-trustworthy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanning Zhang, Juntong Song, Juno Zhu, et al.*2026 · 2 citations*
2. **[RAGVUE: A Diagnostic View for Explainable and Automated Evaluation of Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/murugaraj-2026-ragvue-diagnostic-view-explainable-automated/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Keerthana Murugaraj, Salima Lamsiyah, Martin Theobald*2026 · 1 citation*
3. **[Fahmni at AraHealthQA Track 1: Multi-Agent Retrieval-Augmented Generation and Multi-Label Classification for Arabic Mental Health Q&A](https://md.research.elamur.ai/free/en/papers/sabty-2025-fahmni-arahealthqa-track-1-multi/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Caroline Sabty, Mohamad Rasmy, Mohamed Eyad Badran, et al.*2025 · 1 citation*
4. **[CheckRLM: Effective Knowledge–Thought Coherence Checking in Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-checkrlm-effective-knowledge-thought-coherence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dingling Xu, Ruobing Wang, Qingfei Zhao, et al.*2026*
5. **[Domain-Specific Data Generation Framework for RAG Adaptation](https://md.research.elamur.ai/free/en/papers/tian-2026-domain-specific-data-generation-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chris Xing Tian, Weihao Xie, Zhen Chen, et al.*2026*
6. **[Momoka-RAG: MCTS-Organized Mapping of Knowledge Associations for Long-Document Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/tao-2026-momoka-rag-mcts-organized-mapping/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenyu Tao, Xiaofen Xing, Zeliang Li, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/zhu-2025-rageval-scenario-specific-rag-evaluation/) — RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework