---
title: "Who cites Francois Chollet — 246 papers of our library"
description: "246 papers of the Elamur Research library cite the works of Francois Chollet, found in their bibliographies; the most cited first."
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---
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# Who cites Francois Chollet

246 citations of their works from 246 papers of our library (of the 149,439 whose bibliographies we read) · 41 with a page here, the most cited first · [← Francois Chollet](https://md.research.elamur.ai/free/en/authors/francois-chollet/)

1. **[Transformers: State-of-the-Art Natural Language Processing](https://md.research.elamur.ai/free/en/papers/wolf-2020-transformers-state-art-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thomas Wolf, Lysandre Debut, Victor Sanh, et al.*2020 · 15,755 citations*
2. **[fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://md.research.elamur.ai/free/en/papers/ott-2019-fairseq-fast-extensible-toolkit-sequence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Myle Ott, Sergey Edunov, Alexei Baevski, et al.*2019 · 3,984 citations*
3. **[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*
4. **[Solving Quantitative Reasoning Problems with Language Models](https://md.research.elamur.ai/free/en/papers/lewkowycz-2022-solving-quantitative-reasoning-problems-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Aitor Lewkowycz, Anders Andreassen, David Dohan, et al.*2022 · 992 citations*
5. **[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*
6. **[A Multiscale Visualization of Attention in the Transformer Model](https://md.research.elamur.ai/free/en/papers/vig-2019-multiscale-visualization-attention-transformer-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jesse Vig*2019 · 716 citations*
7. [**Similarity of Neural Network Representations Revisited arXiv:1905.00414**Simon Kornblith, Mohammad Norouzi, Honglak Lee, et al.*2019 · 679 citations*](https://md.research.elamur.ai/free/en/papers/kornblith-2019-similarity-neural-network-representations-revisited/)
8. [**Towards a Human-like Open-Domain Chatbot arXiv:2001.09977**Daniel Adiwardana, Minh-Thang Luong, David R. So, et al.*2020 · 592 citations*](https://md.research.elamur.ai/free/en/papers/adiwardana-2020-towards-human-like-open-domain/)
9. [**Analyzing the Structure of Attention in a Transformer Language Model arXiv:1906.04284**Jesse Vig, Yonatan Belinkov*2019 · 438 citations*](https://md.research.elamur.ai/free/en/papers/vig-2019-analyzing-structure-attention-transformer-language/)
10. [**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/)
11. **[ConveRT: Efficient and Accurate Conversational Representations from Transformers](https://md.research.elamur.ai/free/en/papers/henderson-2020-convert-efficient-accurate-conversational-representations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Matthew Henderson, Iñigo Casanueva, Nikola Mrkšić, et al.*2020 · 269 citations*
12. **[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*
13. **[LeanDojo: Theorem Proving with Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/yang-2023-leandojo-theorem-proving-retrieval-augmented/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.*2023 · 253 citations*
14. **[Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset](https://md.research.elamur.ai/free/en/papers/byrne-2019-taskmaster-1-realistic-diverse-dialog/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bill Byrne, Karthik Krishnamoorthi, Chinnadhurai Sankar, et al.*2019 · 247 citations*
15. [**NeMo: a toolkit for building AI applications using Neural Modules arXiv:1909.09577**Oleksii Kuchaiev, Jason Li, Huyen Nguyen, et al.*2019 · 244 citations*](https://md.research.elamur.ai/free/en/papers/kuchaiev-2019-nemo-toolkit-building-ai-applications/)
16. [**Generative Language Modeling for Automated Theorem Proving arXiv:2009.03393**Stanislas Polu, Ilya Sutskever*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/)
17. **[Hurdles to Progress in Long-form Question Answering](https://md.research.elamur.ai/free/en/papers/krishna-2021-hurdles-progress-long-form-question/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kalpesh Krishna, Aurko Roy, Mohit Iyyer*2021 · 233 citations*
18. [**Autoformalization with Large Language Models arXiv:2205.12615**Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.*2022 · 204 citations*](https://md.research.elamur.ai/free/en/papers/wu-2022-autoformalization-large-language-models/)
19. **[End-to-End Non-Autoregressive Neural Machine Translation with Connectionist Temporal Classification](https://md.research.elamur.ai/free/en/papers/libovicky-2018-end-end-non-autoregressive-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jindřich Libovický, Jindřich Helcl*2018 · 202 citations*
20. **[On NMT Search Errors and Model Errors: Cat Got Your Tongue?](https://md.research.elamur.ai/free/en/papers/stahlberg-2019-nmt-search-errors-model-errors/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Felix Stahlberg, Bill Byrne*2019 · 201 citations*
21. **[Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problem](https://md.research.elamur.ai/free/en/papers/saunders-2020-reducing-gender-bias-neural-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Danielle Saunders, Bill Byrne*2020 · 198 citations*
22. [**Transformers without Tears: Improving the Normalization of Self-Attention arXiv:1910.05895**Toan Q. Nguyen, Julian Salazar*2019 · 189 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2019-transformers-tears-improving-normalization-self/)
23. [**Representation Degeneration Problem in Training Natural Language Generation Models arXiv:1907.12009**Jun Gao, Di He, Xu Tan, et al.*2019 · 181 citations*](https://md.research.elamur.ai/free/en/papers/gao-2019-representation-degeneration-problem-training-natural/)
24. **[Non-Autoregressive Machine Translation with Latent Alignments](https://md.research.elamur.ai/free/en/papers/saharia-2020-non-autoregressive-machine-translation-latent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chitwan Saharia, William Chan, Saurabh Saxena, et al.*2020 · 178 citations*
25. **[A Survey of Machine Learning for Big Code and Naturalness](https://md.research.elamur.ai/free/en/papers/allamanis-2017-survey-machine-learning-big-code/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.*2017 · 167 citations*
26. [**ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics arXiv:2302.12433**Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-proofnet-autoformalizing-formally-proving-undergraduate/)
27. **[Trivial Transfer Learning for Low-Resource Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/kocmi-2018-trivial-transfer-learning-low-resource/) [Conference on Machine Translation: Research Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-research-papers/)**Tom Kocmi, Ondřej Bojar*2018 · 141 citations*
28. [**Deep Network Guided Proof Search arXiv:1701.06972 (In Thomas Eiter and David Sands, editors, 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR-21). EPiC Series in Computing, vol. 46, pages 85-105, EasyChair, 2017. ISSN 2398-7340)**Sarah Loos, Geoffrey Irving, Christian Szegedy, et al.*2017 · 139 citations*](https://md.research.elamur.ai/free/en/papers/loos-2017-deep-network-guided-proof-search/)
29. [**Formal Mathematics Statement Curriculum Learning arXiv:2202.01344**Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.*2022 · 133 citations*](https://md.research.elamur.ai/free/en/papers/polu-2022-formal-mathematics-statement-curriculum-learning/)
30. **[Seq2Edits: Sequence Transduction Using Span-level Edit Operations](https://md.research.elamur.ai/free/en/papers/stahlberg-2020-seq2edits-sequence-transduction-using-span/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Felix Stahlberg, Shankar Kumar*2020 · 133 citations*
31. [**Scaling Up Models and Data with t5x and seqio arXiv:2203.17189**Adam Roberts, Hyung Won Chung, Anselm Levskaya, et al.*2022 · 130 citations*](https://md.research.elamur.ai/free/en/papers/roberts-2022-scaling-up-models-data-texttt/)
32. **[The NiuTrans Machine Translation Systems for WMT19](https://md.research.elamur.ai/free/en/papers/li-2019-niutrans-machine-translation-systems-wmt19/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Bei Li, Yinqiao Li, Chen Xu, et al.*2019 · 92 citations*
33. [**Learning to Prove Theorems via Interacting with Proof Assistants arXiv:1905.09381**Kaiyu Yang, Jia Deng*2019 · 90 citations*](https://md.research.elamur.ai/free/en/papers/yang-2019-learning-prove-theorems-interacting-proof/)
34. [**Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving arXiv:2502.07640**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 84 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-frontier-model-open/)
35. [**LEGO-Prover: Neural Theorem Proving with Growing Libraries arXiv:2310.00656**Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-lego-prover-neural-theorem-proving/)
36. [**Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers arXiv:2205.10893**Albert Q. Jiang, Wenda Li, Szymon Tworkowski, et al.*2022 · 79 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-thor-wielding-hammers-integrate-language/)
37. [**HOList: An Environment for Machine Learning of Higher-Order Theorem Proving arXiv:1904.03241**Kshitij Bansal, Sarah M. Loos, Markus N. Rabe, et al.*2019 · 78 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2019-holist-environment-machine-learning-higher/)
38. [**NaturalProofs: Mathematical Theorem Proving in Natural Language arXiv:2104.01112**Sean Welleck, Jiacheng Liu, Ronan Le Bras, et al.*2021 · 76 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2021-naturalproofs-mathematical-theorem-proving-natural/)
39. **[Findings of the WMT 2019 Biomedical Translation Shared Task: Evaluation for MEDLINE Abstracts and Biomedical Terminologies](https://md.research.elamur.ai/free/en/papers/bawden-2019-findings-wmt-2019-biomedical-translation/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Rachel Bawden, Kevin Bretonnel Cohen, Cristian Grozea, et al.*2019 · 54 citations*
40. **[Premise Selection in Natural Language Mathematical Texts](https://md.research.elamur.ai/free/en/papers/ferreira-2020-premise-selection-natural-language-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deborah Ferreira, André Freitas*2020 · 44 citations*
41. **[Stress Test Evaluation of Transformer-based Models in Natural Language Understanding Tasks](https://md.research.elamur.ai/free/en/papers/aspillaga-2020-stress-test-evaluation-transformer-based/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Carlos Aspillaga, Andrés Carvallo, Vladimir Araujo*2020 · 17 citations*

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

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