---
title: "Who cites Matthieu Devin — 1,535 papers of our library"
description: "1,535 papers of the Elamur Research library cite the works of Matthieu Devin, found in their bibliographies; the most cited first."
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---
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# Who cites Matthieu Devin

1,647 citations of their works from 1,535 papers of our library (of the 149,439 whose bibliographies we read) · 96 with a page here, the most cited first · [← Matthieu Devin](https://md.research.elamur.ai/free/en/authors/matthieu-devin/)

1. [**Very Deep Convolutional Networks for Large-Scale Image Recognition arXiv:1409.1556**Karen Simonyan, Andrew Zisserman*2014 · 73,393 citations*](https://md.research.elamur.ai/free/en/papers/simonyan-2014-very-deep-convolutional-networks-large/)
2. [**Efficient Estimation of Word Representations in Vector Space arXiv:1301.3781**Tomas Mikolov, Kai Chen, Greg Corrado, et al.*2013 · 28,759 citations*](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/)
3. **[Array Programming with NumPy](https://md.research.elamur.ai/free/en/papers/harris-2020-array-programming-numpy/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, et al.*2020 · 23,607 citations*
4. [**Sequence to Sequence Learning with Neural Networks arXiv:1409.3215**Ilya Sutskever, Oriol Vinyals, Quoc V. Le*2014 · 18,409 citations*](https://md.research.elamur.ai/free/en/papers/sutskever-2014-sequence-sequence-learning-neural-networks/)
5. [**Distilling the Knowledge in a Neural Network arXiv:1503.02531**Geoffrey Hinton, Oriol Vinyals, Jeff Dean*2015 · 15,229 citations*](https://md.research.elamur.ai/free/en/papers/hinton-2015-distilling-knowledge-neural-network/)
6. [**TensorFlow: A system for large-scale machine learning arXiv:1605.08695**Martin Abadi, Paul Barham, Jianmin Chen, et al.*2016 · 12,711 citations*](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-system-large-scale-machine/)
7. **[FaceNet: A Unified Embedding for Face Recognition and Clustering](https://md.research.elamur.ai/free/en/papers/schroff-2015-facenet-unified-embedding-face-recognition/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Florian Schroff, Dmitry Kalenichenko, James Philbin*2015 · 12,016 citations*
8. [**TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems arXiv:1603.04467**Martín Abadi, Ashish Agarwal, Paul Barham, et al.*2016 · 9,512 citations*](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-large-scale-machine-learning/)
9. [**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/)
10. [**Explaining and Harnessing Adversarial Examples arXiv:1412.6572**Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy*2014 · 8,577 citations*](https://md.research.elamur.ai/free/en/papers/goodfellow-2014-explaining-harnessing-adversarial-examples/)
11. [**Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks arXiv:1703.03400**Chelsea Finn, Pieter Abbeel, Sergey Levine*2017 · 6,549 citations*](https://md.research.elamur.ai/free/en/papers/finn-2017-model-agnostic-meta-learning-fast/)
12. [**Intriguing properties of neural networks arXiv:1312.6199**Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, et al.*2013 · 5,999 citations*](https://md.research.elamur.ai/free/en/papers/szegedy-2013-intriguing-properties-neural-networks/)
13. [**ADADELTA: An Adaptive Learning Rate Method arXiv:1212.5701**Matthew D. Zeiler*2012 · 5,699 citations*](https://md.research.elamur.ai/free/en/papers/zeiler-2012-adadelta-adaptive-learning-rate-method/)
14. [**Inductive Representation Learning on Large Graphs arXiv:1706.02216**William L. Hamilton, Rex Ying, Jure Leskovec*2017 · 4,795 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2017-inductive-representation-learning-large-graphs/)
15. [**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/)
16. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
17. [**Gemini: A Family of Highly Capable Multimodal Models arXiv:2312.11805**Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.*2023 · 3,050 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2023-gemini-family-highly-capable-multimodal/)
18. **[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*
19. [**What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? arXiv:1703.04977**Alex Kendall, Yarin Gal*2017 · 2,870 citations*](https://md.research.elamur.ai/free/en/papers/kendall-2017-uncertainties-need-bayesian-deep-learning/)
20. **[Attention-based LSTM for Aspect-level Sentiment Classification](https://md.research.elamur.ai/free/en/papers/wang-2016-attention-based-lstm-aspect-level/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yequan Wang, Minlie Huang, Xiaoyan Zhu, et al.*2016 · 2,621 citations*
21. **[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*
22. [**Deep Speech 2: End-to-End Speech Recognition in English and Mandarin arXiv:1512.02595**Dario Amodei, Rishita Anubhai, Eric Battenberg, et al.*2015 · 2,341 citations*](https://md.research.elamur.ai/free/en/papers/amodei-2015-deep-speech-2-end-end/)
23. [**MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems arXiv:1512.01274**Tianqi Chen, Mu Li, Yutian Li, et al.*2015 · 2,000 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-mxnet-flexible-efficient-machine-learning/)
24. **[Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering](https://md.research.elamur.ai/free/en/papers/defferrard-2016-convolutional-neural-networks-graphs-fast/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Michael Defferrard, Xavier Bresson, Pierre Vandergheynst*2016 · 1,861 citations*
25. [**AllenNLP: A Deep Semantic Natural Language Processing Platform arXiv:1803.07640**Matt Gardner, Joel Grus, Mark Neumann, et al.*2018 · 1,819 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2018-allennlp-deep-semantic-natural-language/)
26. [**Layer Normalization arXiv:1607.06450**Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton*2016 · 1,819 citations*](https://md.research.elamur.ai/free/en/papers/ba-2016-layer-normalization/)
27. [**Universal Sentence Encoder arXiv:1803.11175**Daniel Cer, Yinfei Yang, Sheng-yi Kong, et al.*2018 · 1,629 citations*](https://md.research.elamur.ai/free/en/papers/cer-2018-universal-sentence-encoder/)
28. [**Deep Speech: Scaling up end-to-end speech recognition arXiv:1412.5567**Awni Hannun, Carl Case, Jared Casper, et al.*2014 · 1,600 citations*](https://md.research.elamur.ai/free/en/papers/hannun-2014-deep-speech-scaling-up-end/)
29. **[Universal Sentence Encoder for English](https://md.research.elamur.ai/free/en/papers/cer-2018-universal-sentence-encoder-english/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Daniel Cer, Yinfei Yang, Sheng-yi Kong, et al.*2018 · 1,546 citations*
30. [**Zero-Shot Text-to-Image Generation arXiv:2102.12092**Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, et al.*2021 · 1,528 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2021-zero-shot-text-image-generation/)
31. [**Understanding Black-box Predictions via Influence Functions arXiv:1703.04730**Pang Wei Koh, Percy Liang*2017 · 1,514 citations*](https://md.research.elamur.ai/free/en/papers/koh-2017-understanding-black-box-predictions-influence/)
32. **[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*
33. **[Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments](https://md.research.elamur.ai/free/en/papers/anderson-2017-vision-language-navigation-interpreting-visually/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Peter Anderson, Qi Wu, Damien Teney, et al.*2017 · 1,414 citations*
34. [**TVM: An Automated End-to-End Optimizing Compiler for Deep Learning arXiv:1802.04799**Tianqi Chen, Thierry Moreau, Ziheng Jiang, et al.*2018 · 1,384 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-tvm-automated-end-end-optimizing/)
35. [**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/)
36. **[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*
37. [**Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps arXiv:1312.6034**Karen Simonyan, Andrea Vedaldi, Andrew Zisserman*2013 · 1,210 citations*](https://md.research.elamur.ai/free/en/papers/simonyan-2013-deep-inside-convolutional-networks-visualising/)
38. [**DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset arXiv:1710.03957**Yanran Li, Hui Su, Xiaoyu Shen, et al.*2017 · 1,206 citations*](https://md.research.elamur.ai/free/en/papers/li-2017-dailydialog-manually-labelled-multi-turn/)
39. [**PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation ASPLOS 2024**Jason Ansel, Edward Yang, Horace He, et al.*2024 · 946 citations*](https://md.research.elamur.ai/free/en/papers/ansel-2024-pytorch-2-faster-machine-learning/)
40. **[Grounded Compositional Semantics for Finding and Describing Images with Sentences](https://md.research.elamur.ai/free/en/papers/socher-2014-grounded-compositional-semantics-finding-describing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Richard Socher, Andrej Karpathy, Quoc V. Le, et al.*2014 · 932 citations*
41. **[Scaling Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/ott-2018-scaling-neural-machine-translation/) [Conference on Machine Translation: Research Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-research-papers/)**Myle Ott, Sergey Edunov, David Grangier, et al.*2018 · 826 citations*
42. [**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/)
43. [**Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations MAPL 2019**Philippe Tillet, H. T. Kung, David Cox*2019 · 729 citations*](https://md.research.elamur.ai/free/en/papers/tillet-2019-triton-intermediate-language-compiler-tiled/)
44. [**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/)
45. **[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*
46. **[Multilingual Universal Sentence Encoder for Semantic Retrieval](https://md.research.elamur.ai/free/en/papers/yang-2020-multilingual-universal-sentence-encoder-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinfei Yang, Daniel Cer, Amin Ahmad, et al.*2020 · 570 citations*
47. **[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*
48. [**HDLTex: Hierarchical Deep Learning for Text Classification ICMLA 2017**Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, et al.*2017 · 532 citations*](https://md.research.elamur.ai/free/en/papers/kowsari-2017-hdltex-hierarchical-deep-learning-text/)
49. [**GLaM: Efficient Scaling of Language Models with Mixture-of-Experts arXiv:2112.06905**Nan Du, Yanping Huang, Andrew M. Dai, et al.*2021 · 496 citations*](https://md.research.elamur.ai/free/en/papers/du-2021-glam-efficient-scaling-language-models/)
50. [**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/)
51. [**Texygen: A Benchmarking Platform for Text Generation Models arXiv:1802.01886**Yaoming Zhu, Sidi Lu, Lei Zheng, et al.*2018 · 495 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2018-texygen-benchmarking-platform-text-generation/)
52. [**DyNet: The Dynamic Neural Network Toolkit arXiv:1701.03980**Graham Neubig, Chris Dyer, Yoav Goldberg, et al.*2017 · 489 citations*](https://md.research.elamur.ai/free/en/papers/neubig-2017-dynet-dynamic-neural-network-toolkit/)
53. [**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/)
54. [**Adversarial Training Methods for Semi-Supervised Text Classification arXiv:1605.07725**Takeru Miyato, Andrew M. Dai, Ian Goodfellow*2016 · 433 citations*](https://md.research.elamur.ai/free/en/papers/miyato-2016-adversarial-training-methods-semi-supervised/)
55. [**Deep Learning: A Critical Appraisal arXiv:1801.00631**Gary Marcus*2018 · 417 citations*](https://md.research.elamur.ai/free/en/papers/marcus-2018-deep-learning-critical-appraisal/)
56. **[Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning](https://md.research.elamur.ai/free/en/papers/gordon-2020-compressing-bert-studying-effects-weight/) [Workshop on Representation Learning for NLP](https://md.research.elamur.ai/free/en/venues/repl4nlp/)**Mitchell Gordon, Kevin Duh, Nicholas Andrews*2020 · 407 citations*
57. **[emoji2vec: Learning Emoji Representations from their Description](https://md.research.elamur.ai/free/en/papers/eisner-2016-emoji2vec-learning-emoji-representations-their/) [International Workshop on Natural Language Processing for Social Media](https://md.research.elamur.ai/free/en/venues/socialnlp/)**Ben Eisner, Tim Rocktäschel, Isabelle Augenstein, et al.*2016 · 360 citations*
58. [**ZeRO-Offload: Democratizing Billion-Scale Model Training arXiv:2101.06840**Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, et al.*2021 · 309 citations*](https://md.research.elamur.ai/free/en/papers/ren-2021-zero-offload-democratizing-billion-scale/)
59. [**CLUE: A Chinese Language Understanding Evaluation Benchmark arXiv:2004.05986**Liang Xu, Hai Hu, Xuanwei Zhang, et al.*2020 · 244 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-clue-chinese-language-understanding/)
60. **[From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood](https://md.research.elamur.ai/free/en/papers/guu-2017-language-programs-bridging-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kelvin Guu, Panupong Pasupat, Evan Liu, et al.*2017 · 236 citations*
61. **[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*
62. [**Ring Attention with Blockwise Transformers for Near-Infinite Context arXiv:2310.01889**Hao Liu, Matei Zaharia, Pieter Abbeel*2023 · 212 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-ring-attention-blockwise-transformers-near/)
63. [**Mesh-TensorFlow: Deep Learning for Supercomputers arXiv:1811.02084**Noam Shazeer, Youlong Cheng, Niki Parmar, et al.*2018 · 203 citations*](https://md.research.elamur.ai/free/en/papers/shazeer-2018-mesh-tensorflow-deep-learning-supercomputers/)
64. **[Polyglot: Distributed Word Representations for Multilingual NLP](https://md.research.elamur.ai/free/en/papers/rfou-2013-polyglot-distributed-word-representations-multilingual/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Rami Al-Rfou', Bryan Perozzi, Steven Skiena*2013 · 201 citations*
65. **[Tensor2Tensor for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/vaswani-2018-tensor2tensor-neural-machine-translation/) [Conference of the Association for Machine Translation in the Americas (AMTA)](https://md.research.elamur.ai/free/en/venues/amta/)**Ashish Vaswani, Samy Bengio, Eugene Brevdo, et al.*2018 · 191 citations*
66. [**DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models arXiv:2309.14509**Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/jacobs-2023-deepspeed-ulysses-system-optimizations-enabling/)
67. [**Unsupervised Text Style Transfer using Language Models as Discriminators arXiv:1805.11749**Zichao Yang, Zhiting Hu, Chris Dyer, et al.*2018 · 161 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-unsupervised-text-style-transfer-using/)
68. **[Effective Domain Mixing for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/britz-2017-effective-domain-mixing-neural-machine/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Denny Britz, Quoc Le, Reid Pryzant*2017 · 156 citations*
69. **[ChID: A Large-scale Chinese IDiom Dataset for Cloze Test](https://md.research.elamur.ai/free/en/papers/zheng-2019-chid-large-scale-chinese/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chujie Zheng, Minlie Huang, Aixin Sun*2019 · 119 citations*
70. **[Entity Linking in 100 Languages](https://md.research.elamur.ai/free/en/papers/botha-2020-entity-linking-100-languages/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jan A. Botha, Zifei Shan, Daniel Gillick*2020 · 114 citations*
71. [**TextGrad: Automatic "Differentiation" via Text arXiv:2406.07496**Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.*2024 · 96 citations*](https://md.research.elamur.ai/free/en/papers/yuksekgonul-2024-textgrad-automatic-differentiation-text/)
72. **[Finding Skill Neurons in Pre-trained Transformer-based Language Models](https://md.research.elamur.ai/free/en/papers/wang-2022-finding-skill-neurons-pre-trained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaozhi Wang, Kaiyue Wen, Zhengyan Zhang, et al.*2022 · 85 citations*
73. **[Deep Models for Arabic Dialect Identification on Benchmarked Data](https://md.research.elamur.ai/free/en/papers/elaraby-2018-deep-models-arabic-dialect-identification/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Mohamed Elaraby, Muhammad Abdul-Mageed*2018 · 85 citations*
74. **[Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction](https://md.research.elamur.ai/free/en/papers/gerz-2018-language-modeling-morphologically-rich-languages/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Daniela Gerz, Ivan Vulić, Edoardo Ponti, et al.*2018 · 82 citations*
75. [**Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog**Shereen Oraby, Vrindavan Harrison, Amita Misra, et al.*2017 · 70 citations*](https://md.research.elamur.ai/free/en/papers/oraby-2017-are-you-serious-rhetorical-questions/)
76. **[Highly Effective Arabic Diacritization using Sequence to Sequence Modeling](https://md.research.elamur.ai/free/en/papers/mubarak-2019-highly-effective-arabic-diacritization-sequence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hamdy Mubarak, Ahmed Abdelali, Hassan Sajjad, et al.*2019 · 51 citations*
77. [**WebLINX: Real-World Website Navigation with Multi-Turn Dialogue arXiv:2402.05930**Xing Han Lu, Zden\vek Kasner, Siva Reddy*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-weblinx-real-world-website-navigation/)
78. [**Cross-Domain Generalization of Neural Constituency Parsers**Daniel Fried, Nikita Kitaev, Dan Klein*2019 · 46 citations*](https://md.research.elamur.ai/free/en/papers/fried-2019-cross-domain-generalization-neural-constituency/)
79. [**Symbolic Learning Enables Self-Evolving Agents arXiv:2406.18532**Wangchunshu Zhou, Yixin Ou, Shengwei Ding, et al.*2024 · 34 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-symbolic-learning-enables-self-evolving/)
80. **[PropSegmEnt: A Large-Scale Corpus for Proposition-Level Segmentation and Entailment Recognition](https://md.research.elamur.ai/free/en/papers/chen-2023-propsegment-large-scale-corpus-proposition/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sihao Chen, Senaka Buthpitiya, Alex Fabrikant, et al.*2023 · 31 citations*
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