---
title: "Who cites Hua Ren Wu — 2,904 papers of our library"
description: "2,904 papers of the Elamur Research library cite the works of Hua Ren Wu, found in their bibliographies · page 1 of 5 · 1–100; the most cited first."
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---
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# Who cites Hua Ren Wu

3,374 citations of their works from 2,904 papers of our library (of the 149,439 whose bibliographies we read) · 436 with a page here, the most cited first · page 1 of 5 · 1–100 · [← Hua Ren Wu](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/)

**1** [2](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/2/) … [5](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/5/) [next →](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/2/)

1. [**RoBERTa: A Robustly Optimized BERT Pretraining Approach arXiv:1907.11692**Yinhan Liu, Myle Ott, Naman Goyal, et al.*2019 · 9,837 citations*](https://md.research.elamur.ai/free/en/papers/liu-2019-roberta-robustly-optimized-bert-pretraining/)
2. [**Learning Transferable Visual Models From Natural Language Supervision arXiv:2103.00020**Alec Radford, Jong Wook Kim, Chris Hallacy, et al.*2021 · 8,767 citations*](https://md.research.elamur.ai/free/en/papers/radford-2021-learning-transferable-visual-models-natural/)
3. **[Survey of Hallucination in Natural Language Generation](https://md.research.elamur.ai/free/en/papers/ji-2022-survey-hallucination-natural-language-generation/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Ziwei Ji, Nayeon Lee, Rita Frieske, et al.*2022 · 5,974 citations*
4. **[Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://md.research.elamur.ai/free/en/papers/liu-2021-pre-train-prompt-predict-systematic/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al.*2021 · 5,423 citations*
5. [**Neural Architecture Search with Reinforcement Learning arXiv:1611.01578**Barret Zoph, Quoc V. Le*2016 · 4,413 citations*](https://md.research.elamur.ai/free/en/papers/zoph-2016-neural-architecture-search-reinforcement-learning/)
6. **[Natural Questions: A Benchmark for Question Answering Research](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2019-natural-questions-benchmark-question-answering/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, et al.*2019 · 4,093 citations*
7. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
8. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
9. **[SpanBERT: Improving Pre-training by Representing and Predicting Spans](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Mandar Joshi, Danqi Chen, Yinhan Liu, et al.*2019 · 2,616 citations*
10. **[Incorporating Copying Mechanism in Sequence-to-Sequence Learning](https://md.research.elamur.ai/free/en/papers/gu-2016-incorporating-copying-mechanism-sequence-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiatao Gu, Zhengdong Lu, Hang Li, et al.*2016 · 1,915 citations*
11. [**DeBERTa: Decoding-enhanced BERT with Disentangled Attention arXiv:2006.03654**Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 1,828 citations*](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/)
12. [**Pre-trained Models for Natural Language Processing: A Survey arXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
13. [**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/)
14. **[Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision](https://md.research.elamur.ai/free/en/papers/jia-2021-scaling-up-visual-vision-language/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Chao Jia, Yinfei Yang, Ye Xia, et al.*2021 · 1,615 citations*
15. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,556 citations*
16. **[Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,551 citations*
17. [**BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation arXiv:2201.12086**Junnan Li, Dongxu Li, Caiming Xiong, et al.*2022 · 1,523 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-blip-bootstrapping-language-image-pre/)
18. **[Pre-Training with Whole Word Masking for Chinese BERT](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/) [IEEE/ACM Transactions on Audio Speech and Language Processing](https://md.research.elamur.ai/free/en/venues/ieee-acm-transactions-on-audio-speech-and-language-processing/)**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2019 · 1,490 citations*
19. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
20. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
21. [**M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation arXiv:2402.03216**Jianlv Chen, Shitao Xiao, Peitian Zhang, et al.*2024 · 1,196 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-m3-embedding-multi-linguality/)
22. [**MS MARCO: A Human Generated MAchine Reading COmprehension Dataset arXiv:1611.09268**Payal Bajaj, Daniel Campos, Nick Craswell, et al.*2016 · 1,138 citations*](https://md.research.elamur.ai/free/en/papers/bajaj-2016-ms-marco-human-generated/)
23. [**RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space arXiv:1902.10197**Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, et al.*2019 · 1,073 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-rotate-knowledge-graph-embedding-relational/)
24. **[Adversarial Learning for Neural Dialogue Generation](https://md.research.elamur.ai/free/en/papers/li-2017-adversarial-learning-neural-dialogue-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiwei Li, Will Monroe, Tianlin Shi, et al.*2017 · 1,063 citations*
25. **[K-BERT: Enabling Language Representation with Knowledge Graph](https://md.research.elamur.ai/free/en/papers/liu-2019-k-bert-enabling-language-representation/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Weijie Liu, Peng Zhou, Zhe Zhao, et al.*2019 · 1,019 citations*
26. **[ERNIE 2.0: A Continual Pre-training Framework for Language Understanding](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-2-0-continual/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yu Sun, Shuohuan Wang, Yukun Li, et al.*2019 · 995 citations*
27. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
28. [**Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond arXiv:2308.12966**Jinze Bai, Shuai Bai, Shusheng Yang, et al.*2023 · 970 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/)
29. **[Modeling Coverage for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/tu-2016-modeling-coverage-neural-machine-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaopeng Tu, Zhengdong Lu, Yang Liu, et al.*2016 · 939 citations*
30. **[C-Pack: Packed Resources For General Chinese Embeddings](https://md.research.elamur.ai/free/en/papers/xiao-2023-c-pack-packed-resources/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Shitao Xiao, Zheng Liu, Peitian Zhang, et al.*2023 · 922 citations*
31. [**Unsupervised Dense Information Retrieval with Contrastive Learning arXiv:2112.09118**Gautier Izacard, Mathilde Caron, Lucas Hosseini, et al.*2021 · 836 citations*](https://md.research.elamur.ai/free/en/papers/izacard-2021-unsupervised-dense-information-retrieval-contrastive/)
32. **[Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism](https://md.research.elamur.ai/free/en/papers/firat-2016-multi-way-multilingual-neural-machine/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Orhan Firat, Kyunghyun Cho, Yoshua Bengio*2016 · 833 citations*
33. **[GPT-NeoX-20B: An Open-Source Autoregressive Language Model](https://md.research.elamur.ai/free/en/papers/black-2022-gpt-neox-20b-open-source/) [BigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language Models](https://md.research.elamur.ai/free/en/venues/bigscience/)**Sidney Black, Stella Biderman, Eric Hallahan, et al.*2022 · 831 citations*
34. **[Is ChatGPT a General-Purpose Natural Language Processing Task Solver?](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.*2023 · 828 citations*
35. [**ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision arXiv:2102.03334**Wonjae Kim, Bokyung Son, Ildoo Kim*2021 · 804 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-vilt-vision-language-transformer-convolution/)
36. **[Multi-Task Learning for Multiple Language Translation](https://md.research.elamur.ai/free/en/papers/dong-2015-multi-task-learning-multiple-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daxiang Dong, Hua Wu, Wei He, et al.*2015 · 796 citations*
37. **[Explainability for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhao-2023-explainability-large-language-models-survey/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Haiyan Zhao, Hanjie Chen, Fan Yang, et al.*2023 · 790 citations*
38. [**Revisiting Pre-Trained Models for Chinese Natural Language Processing arXiv:2004.13922**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2020 · 790 citations*](https://md.research.elamur.ai/free/en/papers/cui-2020-revisiting-pre-trained-models-chinese/)
39. **[MLQA: Evaluating Cross-lingual Extractive Question Answering](https://md.research.elamur.ai/free/en/papers/lewis-2019-mlqa-evaluating-cross-lingual-extractive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Patrick Lewis, Barlas Oğuz, Ruty Rinott, et al.*2019 · 747 citations*
40. **[Learning To Retrieve Prompts for In-Context Learning](https://md.research.elamur.ai/free/en/papers/rubin-2021-learning-retrieve-prompts-context-learning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ohad Rubin, Jonathan Herzig, Jonathan Berant*2021 · 724 citations*
41. **[TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data](https://md.research.elamur.ai/free/en/papers/yin-2020-tabert-pretraining-joint-understanding-textual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al.*2020 · 692 citations*
42. **[Findings of the 2017 Conference on Machine Translation (WMT17)](https://md.research.elamur.ai/free/en/papers/bojar-2017-findings-2017-conference-machine-translation/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.*2017 · 691 citations*
43. [**Well-Read Students Learn Better: On the Importance of Pre-training Compact Models arXiv:1908.08962**Iulia Turc, Ming-Wei Chang, Kenton Lee, et al.*2019 · 678 citations*](https://md.research.elamur.ai/free/en/papers/turc-2019-well-read-students-learn-better/)
44. **[Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings](https://md.research.elamur.ai/free/en/papers/saxena-2020-improving-multi-hop-question-answering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Apoorv Saxena, Aditay Tripathi, Partha Talukdar*2020 · 671 citations*
45. [**Unsupervised Machine Translation Using Monolingual Corpora Only arXiv:1711.00043**Guillaume Lample, Alexis Conneau, Ludovic Denoyer, et al.*2017 · 669 citations*](https://md.research.elamur.ai/free/en/papers/lample-2017-unsupervised-machine-translation-using-monolingual/)
46. **[Benchmarking Large Language Models in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/chen-2023-benchmarking-large-language-models-retrieval/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Jiawei Chen, Hongyu Lin, Xianpei Han, et al.*2023 · 629 citations*
47. **[RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/qu-2021-rocketqa-optimized-training-approach-dense/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yingqi Qu, Yuchen Ding, Jing Liu, et al.*2021 · 603 citations*
48. [**Text Embeddings by Weakly-Supervised Contrastive Pre-training arXiv:2212.03533**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2022 · 598 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-text-embeddings-weakly-supervised-contrastive/)
49. **[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*
50. [**Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges arXiv:1907.05019**Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.*2019 · 564 citations*](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-massively-multilingual-neural-machine-translation/)
51. **[Precise Zero-Shot Dense Retrieval without Relevance Labels](https://md.research.elamur.ai/free/en/papers/gao-2022-precise-zero-shot-dense-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luyu Gao, Xueguang Ma, Jimmy Lin, et al.*2022 · 549 citations*
52. **[Simple, Scalable Adaptation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/bapna-2019-simple-scalable-adaptation-neural-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ankur Bapna, Orhan Firat*2019 · 530 citations*
53. [**LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding arXiv:2308.14508**Yushi Bai, Xin Lv, Jiajie Zhang, et al.*2023 · 514 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-longbench-bilingual-multitask-benchmark/)
54. [**Neural Text Generation with Unlikelihood Training arXiv:1908.04319**Sean Welleck, Ilia Kulikov, Stephen Roller, et al.*2019 · 513 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2019-neural-text-generation-unlikelihood-training/)
55. **[SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking](https://md.research.elamur.ai/free/en/papers/formal-2021-splade-sparse-lexical-expansion/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Thibault Formal, Benjamin Piwowarski, Stéphane Clinchant*2021 · 512 citations*
56. [**REPLUG: Retrieval-Augmented Black-Box Language Models arXiv:2301.12652**Weijia Shi, Sewon Min, Michihiro Yasunaga, et al.*2023 · 492 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-replug-retrieval-augmented-black-box/)
57. **[ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction](https://md.research.elamur.ai/free/en/papers/santhanam-2022-colbertv2-effective-efficient-retrieval-lightweight/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, et al.*2022 · 485 citations*
58. [**SimVLM: Simple Visual Language Model Pretraining with Weak Supervision arXiv:2108.10904**Zirui Wang, Jiahui Yu, Adams Wei Yu, et al.*2021 · 481 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-simvlm-simple-visual-language-model/)
59. **[Legal Judgment Prediction via Topological Learning](https://md.research.elamur.ai/free/en/papers/zhong-2018-legal-judgment-prediction-topological-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Haoxi Zhong, Zhipeng Guo, Cunchao Tu, et al.*2018 · 480 citations*
60. **[Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation](https://md.research.elamur.ai/free/en/papers/zhang-2020-improving-massively-multilingual-neural-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Biao Zhang, Philip Williams, Ivan Titov, et al.*2020 · 477 citations*
61. **[When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine Translation?](https://md.research.elamur.ai/free/en/papers/qi-2018-when-why-are-pre-trained/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ye Qi, Devendra Sachan, Matthieu Felix, et al.*2018 · 474 citations*
62. [**OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework arXiv:2202.03052**Peng Wang, An Yang, Rui Men, et al.*2022 · 467 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-ofa-unifying-architectures-tasks-modalities/)
63. [**Ethical and social risks of harm from Language Models arXiv:2112.04359**Laura Weidinger, John Mellor, Maribeth Rauh, et al.*2021 · 456 citations*](https://md.research.elamur.ai/free/en/papers/weidinger-2021-ethical-social-risks-harm-language/)
64. **[Deep Keyphrase Generation](https://md.research.elamur.ai/free/en/papers/meng-2017-deep-keyphrase-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Meng, Sanqiang Zhao, Shuguang Han, et al.*2017 · 454 citations*
65. **[Improving Text Embeddings with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-improving-text-embeddings-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2024 · 437 citations*
66. **[Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs](https://md.research.elamur.ai/free/en/papers/li-2023-llm-already-serve-database-interface/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jinyang Li, Binyuan Hui, Ge Qu, et al.*2023 · 433 citations*
67. **[Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling](https://md.research.elamur.ai/free/en/papers/hofstatter-2021-efficiently-teaching-effective-dense-retriever/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Sebastian Hofstatter, Sheng-Chieh Lin, Jheng-Hong Yang, et al.*2021 · 425 citations*
68. **[Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network](https://md.research.elamur.ai/free/en/papers/zhou-2018-multi-turn-response-selection-chatbots/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangyang Zhou, Lu Li, Daxiang Dong, et al.*2018 · 410 citations*
69. **[Exploiting Source-side Monolingual Data in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2016-exploiting-source-side-monolingual-data/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiajun Zhang, Chengqing Zong*2016 · 409 citations*
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