---
title: "Who cites Jason Smith — 1,937 papers of our library"
description: "1937 papers of the Elamur Research library cite the works of Jason Smith, found in their bibliographies · page 1 of 4 · 1–100; the most cited first."
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# Who cites Jason Smith

1,949 citations of their works from 1,937 papers of our library (of the 149,439 whose bibliographies we read) · 349 with a page here, the most cited first · page 1 of 4 · 1–100 · [← Jason Smith](https://md.research.elamur.ai/free/en/authors/jason-smith/)

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1. **[BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://md.research.elamur.ai/free/en/papers/devlin-2019-bert-pre-training-deep-bidirectional/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jacob Devlin, Ming-Wei Chang, Kenton Lee, et al.*2019 · 56,209 citations*
2. [**Attention Is All You Need arXiv:1706.03762**Ashish Vaswani, Noam Shazeer, Niki Parmar, et al.*2017 · 17,458 citations*](https://md.research.elamur.ai/free/en/papers/vaswani-2017-attention-all-need/)
3. [**Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683**Colin Raffel, Noam Shazeer, Adam Roberts, et al.*2019 · 11,325 citations*](https://md.research.elamur.ai/free/en/papers/raffel-2019-exploring-limits-transfer-learning-unified/)
4. **[A Comprehensive Survey on Graph Neural Networks](https://md.research.elamur.ai/free/en/papers/wu-2019-comprehensive-survey-graph-neural-networks/) [IEEE Transactions on Neural Networks and Learning Systems](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-neural-networks-and-learning-systems/)**Zonghan Wu, Shirui Pan, Fengwen Chen, et al.*2019 · 10,312 citations*
5. **[BioBERT: a pre-trained biomedical language representation model for biomedical text mining](https://md.research.elamur.ai/free/en/papers/lee-2019-biobert-pre-trained-biomedical-language/) [Bioinformatics](https://md.research.elamur.ai/free/en/venues/bioinformatics/)**Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, et al.*2019 · 8,339 citations*
6. [**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/)
7. [**A Call for Clarity in Reporting BLEU Scores**Matt Post*2018 · 4,152 citations*](https://md.research.elamur.ai/free/en/papers/post-2018-call-clarity-reporting-bleu-scores/)
8. [**Neural Message Passing for Quantum Chemistry arXiv:1704.01212**Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, et al.*2017 · 3,793 citations*](https://md.research.elamur.ai/free/en/papers/gilmer-2017-neural-message-passing-quantum-chemistry/)
9. **[SciBERT: A Pretrained Language Model for Scientific Text](https://md.research.elamur.ai/free/en/papers/beltagy-2019-scibert-pretrained-language-model-scientific/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Iz Beltagy, Kyle Lo, Arman Cohan*2019 · 3,582 citations*
10. [**Convolutional Sequence to Sequence Learning arXiv:1705.03122**Jonas Gehring, Michael Auli, David Grangier, et al.*2017 · 3,042 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2017-convolutional-sequence-sequence-learning/)
11. **[CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,967 citations*
12. **[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*
13. **[Self-Attention with Relative Position Representations](https://md.research.elamur.ai/free/en/papers/shaw-2018-self-attention-relative-position-representations/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Peter Shaw, Jakob Uszkoreit, Ashish Vaswani*2018 · 2,848 citations*
14. **[OpenNMT: Open-Source Toolkit for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/klein-2017-opennmt-open-source-toolkit-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guillaume Klein, Yoon Kim, Yuntian Deng, et al.*2017 · 2,475 citations*
15. **[UNITER: UNiversal Image-TExt Representation Learning](https://md.research.elamur.ai/free/en/papers/chen-2019-uniter-universal-image-text-representation/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yen-Chun Chen, Linjie Li, Licheng Yu, et al.*2019 · 2,418 citations*
16. [**ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks arXiv:1908.02265**Jiasen Lu, Dhruv Batra, Devi Parikh, et al.*2019 · 2,302 citations*](https://md.research.elamur.ai/free/en/papers/lu-2019-vilbert-pretraining-task-agnostic-visiolinguistic/)
17. **[Text Summarization with Pretrained Encoders](https://md.research.elamur.ai/free/en/papers/liu-2019-text-summarization-pretrained-encoders/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Liu, Mirella Lapata*2019 · 2,095 citations*
18. **[On Faithfulness and Factuality in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/maynez-2020-faithfulness-factuality-abstractive-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joshua Maynez, Shashi Narayan, Bernd Bohnet, et al.*2020 · 1,857 citations*
19. [**PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization arXiv:1912.08777**Jingqing Zhang, Yao Zhao, Mohammad Saleh, et al.*2019 · 1,828 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-pegasus-pre-training-extracted-gap/)
20. **[ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT](https://md.research.elamur.ai/free/en/papers/khattab-2020-colbert-efficient-effective-passage/) [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/)**Omar Khattab, Matei Zaharia*2020 · 1,789 citations*
21. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
22. [**A Deep Reinforced Model for Abstractive Summarization arXiv:1705.04304**Romain Paulus, Caiming Xiong, Richard Socher*2017 · 1,657 citations*](https://md.research.elamur.ai/free/en/papers/paulus-2017-deep-reinforced-model-abstractive-summarization/)
23. **[Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates](https://md.research.elamur.ai/free/en/papers/kudo-2018-subword-regularization-improving-neural-network/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taku Kudo*2018 · 1,573 citations*
24. [**VisualBERT: A Simple and Performant Baseline for Vision and Language arXiv:1908.03557**Liunian Harold Li, Mark Yatskar, Da Yin, et al.*2019 · 1,568 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-visualbert-simple-performant-baseline-vision/)
25. **[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*
26. **[Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects](https://md.research.elamur.ai/free/en/papers/ni-2019-justifying-recommendations-distantly-labeled-reviews/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jianmo Ni, Jiacheng Li, Julian McAuley*2019 · 1,435 citations*
27. [**Unified Language Model Pre-training for Natural Language Understanding and Generation arXiv:1905.03197**Li Dong, Nan Yang, Wenhui Wang, et al.*2019 · 1,422 citations*](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/)
28. **[VideoBERT: A Joint Model for Video and Language Representation Learning](https://md.research.elamur.ai/free/en/papers/sun-2019-videobert-joint-model-video-language/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Chen Sun, Austin Myers, Carl Vondrick, et al.*2019 · 1,345 citations*
29. [**CTRL: A Conditional Transformer Language Model for Controllable Generation arXiv:1909.05858**Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al.*2019 · 1,291 citations*](https://md.research.elamur.ai/free/en/papers/keskar-2019-ctrl-conditional-transformer-language-model/)
30. [**MASS: Masked Sequence to Sequence Pre-training for Language Generation arXiv:1905.02450**Kaitao Song, Xu Tan, Tao Qin, et al.*2019 · 1,143 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-mass-masked-sequence-sequence-pre/)
31. [**CoNLL-2012 Shared Task: Modeling Multilingual Unrestricted Coreference in OntoNotes**Sameer Pradhan, Alessandro Moschitti, Nianwen Xue, et al.*2012 · 1,067 citations*](https://md.research.elamur.ai/free/en/papers/pradhan-2012-conll-2012-shared-task-modeling/)
32. [**VL-BERT: Pre-training of Generic Visual-Linguistic Representations arXiv:1908.08530**Weijie Su, Xizhou Zhu, Yue Cao, et al.*2019 · 1,066 citations*](https://md.research.elamur.ai/free/en/papers/su-2019-vl-bert-pre-training-generic/)
33. [**ERNIE: Enhanced Representation through Knowledge Integration arXiv:1904.09223**Yu Sun, Shuohuan Wang, Yukun Li, et al.*2019 · 962 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-enhanced-representation-through-knowledge/)
34. **[Bottom-Up Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/gehrmann-2018-bottom-up-abstractive-summarization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sebastian Gehrmann, Yuntian Deng, Alexander Rush*2018 · 947 citations*
35. **[Challenges in Data-to-Document Generation](https://md.research.elamur.ai/free/en/papers/wiseman-2017-challenges-data-document-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sam Wiseman, Stuart M. Shieber, Alexander M. Rush*2017 · 856 citations*
36. [**Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers arXiv:1801.04354**Ji Gao, Jack Lanchantin, Mary Lou Soffa, et al.*2018 · 840 citations*](https://md.research.elamur.ai/free/en/papers/gao-2018-black-box-generation-adversarial-text/)
37. **[Learning Deep Transformer Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2019-learning-deep-transformer-models-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiang Wang, Bei Li, Tong Xiao, et al.*2019 · 810 citations*
38. [**Achieving Human Parity on Automatic Chinese to English News Translation arXiv:1803.05567**Hany Hassan, Anthony Aue, Chang Chen, et al.*2018 · 799 citations*](https://md.research.elamur.ai/free/en/papers/hassan-2018-achieving-human-parity-automatic-chinese/)
39. [**Non-Autoregressive Neural Machine Translation arXiv:1711.02281**Jiatao Gu, James Bradbury, Caiming Xiong, et al.*2017 · 793 citations*](https://md.research.elamur.ai/free/en/papers/gu-2017-non-autoregressive-neural-machine-translation/)
40. [**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/)
41. **[Colorless Green Recurrent Networks Dream Hierarchically](https://md.research.elamur.ai/free/en/papers/gulordava-2018-colorless-green-recurrent-networks-dream/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kristina Gulordava, Piotr Bojanowski, Edouard Grave, et al.*2018 · 765 citations*
42. **[Findings of the 2018 Conference on Machine Translation (WMT18)](https://md.research.elamur.ai/free/en/papers/bojar-2018-findings-2018-conference-machine-translation/) [Conference on Machine Translation: Shared Task Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-shared-task-papers/)**Ondřej Bojar, Christian Federmann, Mark Fishel, et al.*2018 · 753 citations*
43. **[A Novel Cascade Binary Tagging Framework for Relational Triple Extraction](https://md.research.elamur.ai/free/en/papers/wei-2020-novel-cascade-binary-tagging-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhepei Wei, Jianlin Su, Yue Wang, et al.*2020 · 736 citations*
44. **[SPECTER: Document-level Representation Learning using Citation-informed Transformers](https://md.research.elamur.ai/free/en/papers/cohan-2020-specter-document-level-representation-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arman Cohan, Sergey Feldman, Iz Beltagy, et al.*2020 · 697 citations*
45. [**The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks arXiv:1802.08232**Nicholas Carlini, Chang Liu, Ulfar Erlingsson, et al.*2018 · 692 citations*](https://md.research.elamur.ai/free/en/papers/carlini-2018-secret-sharer-evaluating-testing-unintended/)
46. [**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/)
47. **[Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging](https://md.research.elamur.ai/free/en/papers/reimers-2017-reporting-score-distributions-makes-difference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nils Reimers, Iryna Gurevych*2017 · 652 citations*
48. **[LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding](https://md.research.elamur.ai/free/en/papers/xu-2021-layoutlmv2-multi-modal-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Xu, Yiheng Xu, Tengchao Lv, et al.*2021 · 627 citations*
49. [**BloombergGPT: A Large Language Model for Finance arXiv:2303.17564**Shijie Wu, Ozan Irsoy, Steven Lu, et al.*2023 · 618 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-bloomberggpt-large-language-model-finance/)
50. [**What do you learn from context? Probing for sentence structure in contextualized word representations arXiv:1905.06316**Ian Tenney, Patrick Xia, Berlin Chen, et al.*2019 · 602 citations*](https://md.research.elamur.ai/free/en/papers/tenney-2019-learn-context-probing-sentence-structure/)
51. [**QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension arXiv:1804.09541**Adams Wei Yu, David Dohan, Minh-Thang Luong, et al.*2018 · 597 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-qanet-combining-local-convolution-global/)
52. **[PAWS: Paraphrase Adversaries from Word Scrambling](https://md.research.elamur.ai/free/en/papers/zhang-2019-paws-paraphrase-adversaries-word-scrambling/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yuan Zhang, Jason Baldridge, Luheng He*2019 · 596 citations*
53. **[Massive Exploration of Neural Machine Translation Architectures](https://md.research.elamur.ai/free/en/papers/britz-2017-massive-exploration-neural-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Denny Britz, Anna Goldie, Minh-Thang Luong, et al.*2017 · 574 citations*
54. **[Leveraging Pre-trained Checkpoints for Sequence Generation Tasks](https://md.research.elamur.ai/free/en/papers/rothe-2019-leveraging-pre-trained-checkpoints-sequence/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Sascha Rothe, Shashi Narayan, Aliaksei Severyn*2019 · 564 citations*
55. [**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/)
56. **[The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chen-2018-best-both-worlds-combining-recent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mia Xu Chen, Orhan Firat, Ankur Bapna, et al.*2018 · 559 citations*
57. **[Fully Character-Level Neural Machine Translation without Explicit Segmentation](https://md.research.elamur.ai/free/en/papers/lee-2017-fully-character-level-neural-machine/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jason Lee, Kyunghyun Cho, Thomas Hofmann*2017 · 553 citations*
58. [**The Natural Language Decathlon: Multitask Learning as Question Answering arXiv:1806.08730**Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, et al.*2018 · 545 citations*](https://md.research.elamur.ai/free/en/papers/mccann-2018-natural-language-decathlon-multitask-learning/)
59. **[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*
60. **[Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search](https://md.research.elamur.ai/free/en/papers/hokamp-2017-lexically-constrained-decoding-sequence-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chris Hokamp, Qun Liu*2017 · 524 citations*
61. [**Regularizing Neural Networks by Penalizing Confident Output Distributions arXiv:1701.06548**Gabriel Pereyra, George Tucker, Jan Chorowski, et al.*2017 · 496 citations*](https://md.research.elamur.ai/free/en/papers/pereyra-2017-regularizing-neural-networks-penalizing-confident/)
62. **[A Convolutional Encoder Model for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gehring-2017-convolutional-encoder-model-neural-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jonas Gehring, Michael Auli, David Grangier, et al.*2017 · 492 citations*
63. **[What do Neural Machine Translation Models Learn about Morphology?](https://md.research.elamur.ai/free/en/papers/belinkov-2017-what-do-neural-machine-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, et al.*2017 · 487 citations*
64. **[HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training](https://md.research.elamur.ai/free/en/papers/li-2020-hero-hierarchical-encoder-video-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Linjie Li, Yen-Chun Chen, Yu Cheng, et al.*2020 · 481 citations*
65. [**ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic arXiv:2101.01785 · ACL-2021 camera ready version**Muhammad Abdul-Mageed, AbdelRahim Elmadany, El Moatez Billah Nagoudi*2021 · 478 citations*](https://md.research.elamur.ai/free/en/papers/abdul-mageed-2021-arbert-marbert-deep-bidirectional-transformers/)
66. **[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*
67. [**Learning to Generate Reviews and Discovering Sentiment arXiv:1704.01444**Alec Radford, Rafal Jozefowicz, Ilya Sutskever*2017 · 474 citations*](https://md.research.elamur.ai/free/en/papers/radford-2017-learning-generate-reviews-discovering-sentiment/)
68. [**Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT arXiv:1904.09077**Shijie Wu, Mark Dredze*2019 · 471 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-beto-bentz-becas-surprising-cross/)
69. **[Hierarchical Transformers for Multi-Document Summarization](https://md.research.elamur.ai/free/en/papers/liu-2019-hierarchical-transformers-multi-document-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Liu, Mirella Lapata*2019 · 468 citations*
70. **[From Zero to Hero: On the Limitations of Zero-Shot Language Transfer with Multilingual Transformers](https://md.research.elamur.ai/free/en/papers/lauscher-2020-zero-hero-limitations-zero-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anne Lauscher, Vinit Ravishankar, Ivan Vulić, et al.*2020 · 463 citations*
71. **[AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback](https://md.research.elamur.ai/free/en/papers/dubois-2023-alpacafarm-simulation-framework-methods-that/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yann Dubois, Xuechen Li, Rohan Taori, et al.*2023 · 456 citations*
72. **[Exploring Pre-trained Language Models for Event Extraction and Generation](https://md.research.elamur.ai/free/en/papers/yang-2019-exploring-pre-trained-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sen Yang, Dawei Feng, Linbo Qiao, et al.*2019 · 454 citations*
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