---
title: "Who cites Unsupervised Cross-lingual — 4,133 citing papers"
description: "4,133 papers of the Elamur Research library cite «Unsupervised Cross-lingual Representation Learning at Scale», found in their…"
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---
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# Who cites «Unsupervised Cross-lingual Representation Learning at Scale»

4,133 papers of our library cite it (of the 149,439 whose bibliographies we read) · 689 with a page here, the most cited first · page 1 of 7 · 1–100 · [← back to «Unsupervised Cross-lingual Representation Learning at Scale»](https://md.research.elamur.ai/free/en/papers/conneau-2020-unsupervised-cross-lingual-representation-learning/)

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1. **[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*
2. **[mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer](https://md.research.elamur.ai/free/en/papers/xue-2021-mt5-massively-multilingual-pre-trained/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Linting Xue, Noah Constant, Adam Roberts, et al.*2021 · 3,226 citations*
3. **[Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference](https://md.research.elamur.ai/free/en/papers/schick-2021-exploiting-cloze-questions-few-shot/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Timo Schick, Hinrich Schütze*2021 · 1,817 citations*
4. [**COMET: A Neural Framework for MT Evaluation**Ricardo Rei, Craig Stewart, Ana C Farinha, et al.*2020 · 1,792 citations*](https://md.research.elamur.ai/free/en/papers/rei-2020-comet-neural-framework-mt-evaluation/)
5. [**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/)
6. [**Qwen Technical Report arXiv:2309.16609**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,669 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/)
7. **[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*
8. **[Language-agnostic BERT Sentence Embedding](https://md.research.elamur.ai/free/en/papers/feng-2020-language-agnostic-bert-sentence-embedding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangxiaoyu Feng, Yinfei Yang, Daniel Cer, et al.*2020 · 1,413 citations*
9. **[Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/reimers-2020-making-monolingual-sentence-embeddings-multilingual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nils Reimers, Iryna Gurevych*2020 · 1,322 citations*
10. [**DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing arXiv:2111.09543**Pengcheng He, Jianfeng Gao, Weizhu Chen*2021 · 1,320 citations*](https://md.research.elamur.ai/free/en/papers/he-2021-debertav3-improving-deberta-using-electra/)
11. [**AraBERT: Transformer-based Model for Arabic Language Understanding arXiv:2003.00104**Wissam Antoun, Fady Baly, Hazem Hajj*2020 · 1,304 citations*](https://md.research.elamur.ai/free/en/papers/antoun-2020-arabert-transformer-based-model-arabic/)
12. **[CamemBERT: a Tasty French Language Model](https://md.research.elamur.ai/free/en/papers/martin-2019-camembert-tasty-french-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, et al.*2019 · 1,269 citations*
13. [**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/)
14. **[BERTweet: A pre-trained language model for English Tweets](https://md.research.elamur.ai/free/en/papers/nguyen-2020-bertweet-pre-trained-language-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dat Quoc Nguyen, Thanh Vu, Anh Tuan Nguyen*2020 · 1,144 citations*
15. **[Bias and Fairness in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/gallegos-2023-bias-fairness-large-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.*2023 · 1,082 citations*
16. **[MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer](https://md.research.elamur.ai/free/en/papers/pfeiffer-2020-mad-x-adapter-based-framework/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jonas Pfeiffer, Ivan Vulić, Iryna Gurevych, et al.*2020 · 839 citations*
17. [**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/)
18. **[XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale](https://md.research.elamur.ai/free/en/papers/babu-2021-xls-r-self-supervised-cross/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Arun Babu, Changhan Wang, Andros Tjandra, et al.*2021 · 807 citations*
19. **[LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking](https://md.research.elamur.ai/free/en/papers/huang-2022-layoutlmv3-pre-training-document-ai/) [ACM International Conference on Multimedia (ACM MM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-multimedia-acm-mm/)**Yupan Huang, Tengchao Lv, Lei Cui, et al.*2022 · 778 citations*
20. **[Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.*2021 · 750 citations*
21. **[IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages](https://md.research.elamur.ai/free/en/papers/kakwani-2020-indicnlpsuite-monolingual-corpora-evaluation-benchmarks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Divyanshu Kakwani, Anoop Kunchukuttan, Satish Golla, et al.*2020 · 732 citations*
22. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 703 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
23. **[PhoBERT: Pre-trained language models for Vietnamese](https://md.research.elamur.ai/free/en/papers/nguyen-2020-phobert-pre-trained-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dat Quoc Nguyen, Anh Tuan Nguyen*2020 · 571 citations*
24. [**XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization arXiv:2003.11080**Junjie Hu, Sebastian Ruder, Aditya Siddhant, et al.*2020 · 558 citations*](https://md.research.elamur.ai/free/en/papers/hu-2020-xtreme-massively-multilingual-multi-task/)
25. **[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*
26. **[Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning](https://md.research.elamur.ai/free/en/papers/aghajanyan-2021-intrinsic-dimensionality-explains-effectiveness-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Armen Aghajanyan, Sonal Gupta, Luke Zettlemoyer*2021 · 542 citations*
27. [**Few-shot Learning with Multilingual Language Models arXiv:2112.10668**Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, et al.*2021 · 500 citations*](https://md.research.elamur.ai/free/en/papers/lin-2021-few-shot-learning-multilingual-language/)
28. [**Language Models are Multilingual Chain-of-Thought Reasoners arXiv:2210.03057**Freda Shi, Mirac Suzgun, Markus Freitag, et al.*2022 · 494 citations*](https://md.research.elamur.ai/free/en/papers/shi-2022-language-models-multilingual-chain-thought/)
29. [**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/)
30. **[XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/ponti-2020-xcopa-multilingual-dataset-causal-commonsense/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Edoardo Maria Ponti, Goran Glavaš, Olga Majewska, et al.*2020 · 469 citations*
31. **[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*
32. **[Are All Languages Created Equal in Multilingual BERT?](https://md.research.elamur.ai/free/en/papers/wu-2020-are-all-languages-created-equal/) [Workshop on Representation Learning for NLP](https://md.research.elamur.ai/free/en/venues/repl4nlp/)**Shijie Wu, Mark Dredze*2020 · 460 citations*
33. **[Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets](https://md.research.elamur.ai/free/en/papers/kreutzer-2021-quality-glance-audit-web-crawled/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Julia Kreutzer, Isaac Caswell, Lisa Wang, et al.*2021 · 454 citations*
34. **[How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models](https://md.research.elamur.ai/free/en/papers/rust-2021-how-good-is-your-tokenizer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Phillip Rust, Jonas Pfeiffer, Ivan Vulić, et al.*2021 · 449 citations*
35. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 443 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
36. **[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*
37. **[The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale](https://md.research.elamur.ai/free/en/papers/penedo-2024-fineweb-datasets-decanting-web-finest/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al.*2024 · 434 citations*
38. **[ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 422 citations*
39. [**MuRIL: Multilingual Representations for Indian Languages arXiv:2103.10730**Simran Khanuja, Diksha Bansal, Sarvesh Mehtani, et al.*2021 · 408 citations*](https://md.research.elamur.ai/free/en/papers/khanuja-2021-muril-multilingual-representations-indian-languages/)
40. **[A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios](https://md.research.elamur.ai/free/en/papers/hedderich-2021-survey-recent-approaches-natural-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Michael A. Hedderich, Lukas Lange, Heike Adel, et al.*2021 · 401 citations*
41. **[German's Next Language Model](https://md.research.elamur.ai/free/en/papers/chan-2020-german-s-next-language-model/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Branden Chan, Stefan Schweter, Timo Möller*2020 · 385 citations*
42. **[XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation](https://md.research.elamur.ai/free/en/papers/liang-2020-xglue-new-benchmark-dataset-cross/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yaobo Liang, Nan Duan, Yeyun Gong, et al.*2020 · 358 citations*
43. **[SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection](https://md.research.elamur.ai/free/en/papers/schlechtweg-2020-semeval-2020-task-1-unsupervised/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, et al.*2020 · 351 citations*
44. [**Multilingual E5 Text Embeddings: A Technical Report arXiv:2402.05672**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2024 · 346 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-multilingual-e5-text-embeddings-technical/)
45. [**Scaling Speech Technology to 1,000+ Languages arXiv:2305.13516**Vineel Pratap, Andros Tjandra, Bowen Shi, et al.*2023 · 334 citations*](https://md.research.elamur.ai/free/en/papers/pratap-2023-scaling-speech-technology-1-000/)
46. **[Unsupervised Domain Clusters in Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/aharoni-2020-unsupervised-domain-clusters-pretrained-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Roee Aharoni, Yoav Goldberg*2020 · 330 citations*
47. **[CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task](https://md.research.elamur.ai/free/en/papers/rei-2022-cometkiwi-ist-unbabel-2022-submission/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Ricardo Rei, Marcos Treviso, Nuno M. Guerreiro, et al.*2022 · 325 citations*
48. **[Probing Pretrained Language Models for Lexical Semantics](https://md.research.elamur.ai/free/en/papers/vulic-2020-probing-pretrained-language-models-lexical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ivan Vulić, Edoardo Maria Ponti, Robert Litschko, et al.*2020 · 320 citations*
49. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
50. **[Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation](https://md.research.elamur.ai/free/en/papers/clark-2022-canine-pre-training-efficient-tokenization/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jonathan H. Clark, Dan Garrette, Iulia Turc, et al.*2022 · 301 citations*
51. [**FlauBERT: Unsupervised Language Model Pre-training for French arXiv:1912.05372**Hang Le, Loïc Vial, Jibril Frej, et al.*2019 · 299 citations*](https://md.research.elamur.ai/free/en/papers/le-2019-flaubert-unsupervised-language-model-pre/)
52. **[BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla](https://md.research.elamur.ai/free/en/papers/bhattacharjee-2022-banglabert-language-model-pretraining-benchmarks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Abhik Bhattacharjee, Tahmid Hasan, Wasi Ahmad, et al.*2022 · 296 citations*
53. [**MEGA: Multilingual Evaluation of Generative AI arXiv:2303.12528**Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.*2023 · 285 citations*](https://md.research.elamur.ai/free/en/papers/ahuja-2023-mega-multilingual-evaluation-generative-ai/)
54. **[XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation](https://md.research.elamur.ai/free/en/papers/ruder-2021-xtreme-r-more-challenging-nuanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sebastian Ruder, Noah Constant, Jan Botha, et al.*2021 · 281 citations*
55. [**InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training arXiv:2007.07834**Zewen Chi, Li Dong, Furu Wei, et al.*2020 · 275 citations*](https://md.research.elamur.ai/free/en/papers/chi-2020-infoxlm-information-theoretic-framework-cross/)
56. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 272 citations*
57. **[XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond](https://md.research.elamur.ai/free/en/papers/barbieri-2022-xlm-t-multilingual-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Francesco Barbieri, Luis Espinosa Anke, Jose Camacho-Collados*2022 · 271 citations*
58. **[IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/wilie-2020-indonlu-benchmark-resources-evaluating-indonesian/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Bryan Wilie, Karissa Vincentio, Genta Indra Winata, et al.*2020 · 266 citations*
59. **[The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://md.research.elamur.ai/free/en/papers/bandarkar-2023-belebele-benchmark-parallel-reading-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lucas Bandarkar, Davis Liang, Benjamin Muller, et al.*2023 · 262 citations*
60. **[Fairseq S2T: Fast Speech-to-Text Modeling with Fairseq](https://md.research.elamur.ai/free/en/papers/wang-2020-fairseq-s2t-fast-speech-text/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Changhan Wang, Yun Tang, Xutai Ma, et al.*2020 · 259 citations*
61. **[The Multilingual Amazon Reviews Corpus](https://md.research.elamur.ai/free/en/papers/keung-2020-multilingual-amazon-reviews-corpus/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Phillip Keung, Yichao Lu, György Szarvas, et al.*2020 · 257 citations*
62. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
63. **[MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark](https://md.research.elamur.ai/free/en/papers/li-2021-mtop-comprehensive-multilingual-task-oriented/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Haoran Li, Abhinav Arora, Shuohui Chen, et al.*2021 · 242 citations*
64. [**BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage arXiv:2208.03188**Kurt Shuster, Jing Xu, Mojtaba Komeili, et al.*2022 · 241 citations*](https://md.research.elamur.ai/free/en/papers/shuster-2022-blenderbot-3-deployed-conversational-agent/)
65. **[Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art](https://md.research.elamur.ai/free/en/papers/lewis-2020-pretrained-language-models-biomedical-clinical/) [Workshop on Clinical Natural Language Processing (Clinical NLP) @ LREC](https://md.research.elamur.ai/free/en/venues/clinicalnlp/)**Patrick Lewis, Myle Ott, Jingfei Du, et al.*2020 · 241 citations*
66. **[SemEval-2020 Task 9: Overview of Sentiment Analysis of Code-Mixed Tweets](https://md.research.elamur.ai/free/en/papers/patwa-2020-semeval-2020-task-9-overview/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Parth Patwa, Gustavo Aguilar, Sudipta Kar, et al.*2020 · 240 citations*
67. **[mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2024-mgte-generalized-long-context-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Zhang, Yanzhao Zhang, Dingkun Long, et al.*2024 · 237 citations*
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