--- title: "Who cites Understanding Dataset Design — 64 citing papers" description: "64 papers of the Elamur Research library cite «Understanding Dataset Design Choices for Multi-hop Reasoning», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/chen-2019-understanding-dataset-design-choices-multi/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/chen-2019-understanding-dataset-design-choices-multi/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Understanding Dataset Design Choices for…](https://md.research.elamur.ai/free/en/papers/chen-2019-understanding-dataset-design-choices-multi/) / cited by # Who cites «Understanding Dataset Design Choices for Multi-hop Reasoning» 64 papers of our library cite it (of the 141,840 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «Understanding Dataset Design Choices for Multi-hop Reasoning»](https://md.research.elamur.ai/free/en/papers/chen-2019-understanding-dataset-design-choices-multi/) 1. [**Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps**Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, et al.*2020 · 735 citations*](https://md.research.elamur.ai/free/en/papers/ho-2020-constructing-multi-hop-qa-dataset/) 2. [**♫ MuSiQue: Multihop Questions via Single-hop Question Composition**Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, et al.*2022 · 384 citations*](https://md.research.elamur.ai/free/en/papers/trivedi-2022-musique-multihop-questions-single-hop/) 3. [**HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data**Wenhu Chen, Hanwen Zha, Zhiyu Chen, et al.*2020 · 377 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-hybridqa-dataset-multi-hop-question/) 4. [**Hierarchical Graph Network for Multi-hop Question Answering**Yuwei Fang, Siqi Sun, Zhe Gan, et al.*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/fang-2020-hierarchical-graph-network-multi-hop/) 5. [**Compositional Questions Do Not Necessitate Multi-hop Reasoning**Sewon Min, Eric Wallace, Sameer Singh, et al.*2019 · 231 citations*](https://md.research.elamur.ai/free/en/papers/min-2019-compositional-questions-do-not-necessitate/) 6. [**HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification**Yichen Jiang, Shikha Bordia, Zheng Zhong, et al.*2020 · 221 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-hover-dataset-many-hop-fact/) 7. [**Break It Down: A Question Understanding Benchmark**Tomer Wolfson, Mor Geva, Ankit Gupta, et al.*2020 · 218 citations*](https://md.research.elamur.ai/free/en/papers/wolfson-2020-break-it-down-question-understanding/) 8. [**Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models**Mosh Levy, Alon Jacoby, Yoav Goldberg*2024 · 212 citations*](https://md.research.elamur.ai/free/en/papers/levy-2024-same-task-more-tokens-impact/) 9. [**The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning**Xi Ye, Greg Durrett*2022 · 196 citations*](https://md.research.elamur.ai/free/en/papers/ye-2022-unreliability-explanations-few-shot-prompting/) 10. [**Answering Complex Open-domain Questions Through Iterative Query Generation**Peng Qi, Xiaowen Lin, Leo Mehr, et al.*2019 · 152 citations*](https://md.research.elamur.ai/free/en/papers/qi-2019-answering-complex-open-domain-questions/) 11. [**Look at the First Sentence: Position Bias in Question Answering**Miyoung Ko, Jinhyuk Lee, Hyunjae Kim, et al.*2020 · 102 citations*](https://md.research.elamur.ai/free/en/papers/ko-2020-look-first-sentence-position-bias/) 12. [**Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models**Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/schlegel-2020-leaderboards-survey-methods-revealing-weaknesses/) 13. [**Robustifying Multi-hop QA through Pseudo-Evidentiality Training**Kyungjae Lee, Seung-won Hwang, Sang-eun Han, et al.*2021 · 19 citations*](https://md.research.elamur.ai/free/en/papers/lee-2021-robustifying-multi-hop-qa-through/) 51 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/chen-2019-understanding-dataset-design-choices-multi/) — Understanding Dataset Design Choices for Multi-hop Reasoning