---
title: "Who cites WikiAsp: A Dataset for — 36 citing papers"
description: "36 papers of the Elamur Research library cite «WikiAsp: A Dataset for Multi-domain Aspect-based Summarization», found in their…"
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---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [WikiAsp: A Dataset for Multi-domain Aspect-based…](https://md.research.elamur.ai/free/en/papers/hayashi-2021-wikiasp-dataset-multi-domain-aspect/) / cited by

# Who cites «WikiAsp: A Dataset for Multi-domain Aspect-based Summarization»

36 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 «WikiAsp: A Dataset for Multi-domain Aspect-based Summarization»](https://md.research.elamur.ai/free/en/papers/hayashi-2021-wikiasp-dataset-multi-domain-aspect/)

1. [**Retrieval-Augmented Generation for Large Language Models: A Survey arXiv:2312.10997**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,663 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/)
2. **[Active Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/jiang-2023-active-retrieval-augmented-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhengbao Jiang, Frank Xu, Luyu Gao, et al.*2023 · 872 citations*
3. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
4. **[Dolomites: Domain-Specific Long-Form Methodical Tasks](https://md.research.elamur.ai/free/en/papers/malaviya-2025-dolomites-domain-specific-long-form/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Chaitanya Malaviya, Priyanka Agrawal, Kuzman Ganchev, et al.*2025 · 12 citations*
5. **[RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2025-richrag-crafting-rich-responses-multi/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Shuting Wang, Xin Yu, Mang Wang, et al.*2025 · 10 citations*
6. **[InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in Summarization](https://md.research.elamur.ai/free/en/papers/nishida-2026-instructsum-benchmark-evaluate-instruction-following/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kosuke Nishida, Kyosuke Nishida, Itsumi Saito*2026*

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

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