---
title: "Who cites Xingyu Li — 159 papers of our library"
description: "159 papers of the Elamur Research library cite the works of Xingyu Li, found in their bibliographies; the most cited first."
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---
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# Who cites Xingyu Li

159 citations of their works from 159 papers of our library (of the 149,439 whose bibliographies we read) · 29 with a page here, the most cited first · [← Xingyu Li](https://md.research.elamur.ai/free/en/authors/xingyu-li/)

1. **[Dense Passage Retrieval for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/karpukhin-2020-dense-passage-retrieval-open-domain/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Vladimir Karpukhin, Barlas Oguz, Sewon Min, et al.*2020 · 5,421 citations*
2. **[Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering](https://md.research.elamur.ai/free/en/papers/izacard-2021-leveraging-passage-retrieval-generative-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Gautier Izacard, Edouard Grave*2021 · 1,692 citations*
3. **[Latent Retrieval for Weakly Supervised Open Domain Question Answering](https://md.research.elamur.ai/free/en/papers/lee-2019-latent-retrieval-weakly-supervised-open/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kenton Lee, Ming-Wei Chang, Kristina Toutanova*2019 · 1,253 citations*
4. **[A Robustly Optimized BERT Pre-training Approach with Post-training](https://md.research.elamur.ai/free/en/papers/zhuang-2021-robustly-optimized-bert-pre-training/) [Chinese National Conference on Computational Linguistics](https://md.research.elamur.ai/free/en/venues/ccl/)**Liu Zhuang, Lin Wayne, Shi Ya, et al.*2021 · 587 citations*
5. **[A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge](https://md.research.elamur.ai/free/en/papers/schwenk-2022-okvqa-benchmark-visual-question-answering/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, et al.*2022 · 509 citations*
6. **[Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity](https://md.research.elamur.ai/free/en/papers/jeong-2024-adaptive-rag-learning-adapt-retrieval/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Soyeong Jeong, Jinheon Baek, Sukmin Cho, et al.*2024 · 382 citations*
7. **[Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2019-multi-passage-bert-globally-normalized/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhiguo Wang, Patrick Ng, Xiaofei Ma, et al.*2019 · 303 citations*
8. [**Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering arXiv:1911.10470**Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, et al.*2019 · 280 citations*](https://md.research.elamur.ai/free/en/papers/asai-2019-learning-retrieve-reasoning-paths-over/)
9. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
10. [**How Context Affects Language Models' Factual Predictions arXiv:2005.04611**Fabio Petroni, Patrick Lewis, Aleksandra Piktus, et al.*2020 · 234 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2020-context-affects-language-models-factual/)
11. **[Open-Domain Question Answering Goes Conversational via Question Rewriting](https://md.research.elamur.ai/free/en/papers/anantha-2021-open-domain-question-answering-goes/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Raviteja Anantha, Svitlana Vakulenko, Zhucheng Tu, et al.*2021 · 228 citations*
12. **[Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index](https://md.research.elamur.ai/free/en/papers/seo-2019-real-time-open-domain-question/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minjoon Seo, Jinhyuk Lee, Tom Kwiatkowski, et al.*2019 · 218 citations*
13. **[Simple Entity-Centric Questions Challenge Dense Retrievers](https://md.research.elamur.ai/free/en/papers/sciavolino-2021-simple-entity-centric-questions-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, et al.*2021 · 169 citations*
14. **[UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/oguz-2022-unik-qa-unified-representations-structured/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Barlas Oguz, Xilun Chen, Vladimir Karpukhin, et al.*2022 · 147 citations*
15. **[TopiOCQA: Open-domain Conversational Question Answering with Topic Switching](https://md.research.elamur.ai/free/en/papers/adlakha-2022-topiocqa-open-domain-conversational-question/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vaibhav Adlakha, Shehzaad Dhuliawala, Kaheer Suleman, et al.*2022 · 145 citations*
16. **[Zero-shot Neural Passage Retrieval via Domain-targeted Synthetic Question Generation](https://md.research.elamur.ai/free/en/papers/ma-2021-zero-shot-neural-passage-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ji Ma, Ivan Korotkov, Yinfei Yang, et al.*2021 · 144 citations*
17. **[Open Domain Question Answering over Tables via Dense Retrieval](https://md.research.elamur.ai/free/en/papers/herzig-2021-open-domain-question-answering-over/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jonathan Herzig, Thomas Müller, Syrine Krichene, et al.*2021 · 134 citations*
18. [**Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering arXiv:1911.03868**Sewon Min, Danqi Chen, Luke Zettlemoyer, et al.*2019 · 133 citations*](https://md.research.elamur.ai/free/en/papers/min-2019-knowledge-guided-text-retrieval-reading/)
19. **[Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/chen-2020-open-domain-question-answering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Danqi Chen, Wen-tau Yih*2020 · 129 citations*
20. **[Learning Dense Representations of Phrases at Scale](https://md.research.elamur.ai/free/en/papers/lee-2021-learning-dense-representations-phrases-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinhyuk Lee, Mujeen Sung, Jaewoo Kang, et al.*2021 · 126 citations*
21. [**H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models arXiv:2306.14048**Zhenyu Zhang, Ying Sheng, Tianyi Zhou, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-h-2-o-heavy-hitter/)
22. [**Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model arXiv:1912.09637**Wenhan Xiong, Jingfei Du, William Yang Wang, et al.*2019 · 117 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2019-pretrained-encyclopedia-weakly-supervised-knowledge/)
23. [**Augmented Large Language Models with Parametric Knowledge Guiding arXiv:2305.04757**Ziyang Luo, Can Xu, Pu Zhao, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-augmented-large-language-models-parametric/)
24. [**IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions**Wenhao Yu, Meng Jiang, Peter Clark, et al.*2023 · 26 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-ifqa-dataset-open-domain-question/)
25. **[Transformers to Fight the COVID-19 Infodemic](https://md.research.elamur.ai/free/en/papers/uyangodage-2021-transformers-fight-covid-19-infodemic/) [Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda](https://md.research.elamur.ai/free/en/venues/nlp4if/)**Lasitha Uyangodage, Tharindu Ranasinghe, Hansi Hettiarachchi*2021 · 16 citations*
26. **[Cross-document Event Coreference Search: Task, Dataset and Modeling](https://md.research.elamur.ai/free/en/papers/eirew-2022-cross-document-event-coreference-search/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Alon Eirew, Avi Caciularu, Ido Dagan*2022 · 15 citations*
27. **[Low Resource Question Answering: An Amharic Benchmarking Dataset](https://md.research.elamur.ai/free/en/papers/taffa-2024-low-resource-question-answering-amharic/) [Resources for African Indigenous Languages (RAIL) @ LREC](https://md.research.elamur.ai/free/en/venues/rail/)**Tilahun Abedissa Taffa, Ricardo Usbeck, Yaregal Assabie*2024 · 8 citations*
28. **[Alex-U 2023 NLP at WojoodNER shared task: AraBINDER (Bi-encoder for Arabic Named Entity Recognition)](https://md.research.elamur.ai/free/en/papers/hussein-2023-alex-u-2023-nlp-wojoodner/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Mariam Hussein, Sarah Khaled, Marwan Torki, et al.*2023 · 5 citations*
29. **[ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Charts](https://md.research.elamur.ai/free/en/papers/ye-2026-chartdiff-large-scale-benchmark-comprehending/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Rongtian Ye*2026*

130 more citing papers of our library have no page here yet.

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