---
title: "Who cites Xiangyu Zhang — 6,062 papers of our library"
description: "6,062 papers of the Elamur Research library cite the works of Xiangyu Zhang, found in their bibliographies · page 1 of 5 · 1–100; the most cited first."
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---
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# Who cites Xiangyu Zhang

6,662 citations of their works from 6,062 papers of our library (of the 149,439 whose bibliographies we read) · 464 with a page here, the most cited first · page 1 of 5 · 1–100 · [← Xiangyu Zhang](https://md.research.elamur.ai/free/en/authors/xiangyu-zhang/)

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

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. **[Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://md.research.elamur.ai/free/en/papers/ren-2015-faster-r-cnn-towards-real/) [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-pattern-analysis-and-machine-intelligence/)**Shaoqing Ren, Kaiming He, Ross Girshick, et al.*2015 · 65,090 citations*
3. **[Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://md.research.elamur.ai/free/en/papers/liu-2021-swin-transformer-hierarchical-vision-transformer/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Ze Liu, Yutong Lin, Yue Cao, et al.*2021 · 33,968 citations*
4. [**An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale arXiv:2010.11929**Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, et al.*2020 · 23,726 citations*](https://md.research.elamur.ai/free/en/papers/dosovitskiy-2020-image-worth-16x16-words-transformers/)
5. [**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/)
6. **[Momentum Contrast for Unsupervised Visual Representation Learning](https://md.research.elamur.ai/free/en/papers/he-2019-momentum-contrast-unsupervised-visual-representation/) [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/)**Kaiming He, Haoqi Fan, Yuxin Wu, et al.*2019 · 13,302 citations*
7. [**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/)
8. [**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/)
9. [**YOLOv4: Optimal Speed and Accuracy of Object Detection arXiv:2004.10934**Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao*2020 · 10,403 citations*](https://md.research.elamur.ai/free/en/papers/bochkovskiy-2020-yolov4-optimal-speed-accuracy-object/)
10. **[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*
11. [**MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications arXiv:1704.04861**Andrew G. Howard, Menglong Zhu, Bo Chen, et al.*2017 · 9,729 citations*](https://md.research.elamur.ai/free/en/papers/howard-2017-mobilenets-efficient-convolutional-neural-networks/)
12. [**Deep Residual Learning for Image Recognition arXiv:1512.03385**Kaiming He, Xiangyu Zhang, Shaoqing Ren, et al.*2015 · 9,425 citations*](https://md.research.elamur.ai/free/en/papers/he-2015-deep-residual-learning-image-recognition/)
13. [**Graph Attention Networks arXiv:1710.10903**Petar Veličkovic, Guillem Cucurull, Arantxa Casanova, et al.*2017 · 9,035 citations*](https://md.research.elamur.ai/free/en/papers/veli-vckovic-2017-graph-attention-networks/)
14. [**Semi-Supervised Classification with Graph Convolutional Networks arXiv:1609.02907**Thomas N. Kipf, Max Welling*2016 · 9,023 citations*](https://md.research.elamur.ai/free/en/papers/kipf-2016-semi-supervised-classification-graph-convolutional/)
15. [**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/)
16. [**A Simple Framework for Contrastive Learning of Visual Representations arXiv:2002.05709**Ting Chen, Simon Kornblith, Mohammad Norouzi, et al.*2020 · 8,000 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-simple-framework-contrastive-learning-visual/)
17. [**Representation Learning with Contrastive Predictive Coding arXiv:1807.03748**Aaron van den Oord, Yazhe Li, Oriol Vinyals*2018 · 7,022 citations*](https://md.research.elamur.ai/free/en/papers/oord-2018-representation-learning-contrastive-predictive-coding/)
18. **[Learning Transferable Architectures for Scalable Image Recognition](https://md.research.elamur.ai/free/en/papers/zoph-2017-learning-transferable-architectures-scalable-image/) [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/)**Barret Zoph, Vijay Vasudevan, Jonathon Shlens, et al.*2017 · 6,583 citations*
19. **[Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization](https://md.research.elamur.ai/free/en/papers/selvaraju-2016-grad-cam-visual-explanations-deep/) [International Journal of Computer Vision](https://md.research.elamur.ai/free/en/venues/international-journal-of-computer-vision/)**Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, et al.*2016 · 6,394 citations*
20. **[Emerging Properties in Self-Supervised Vision Transformers](https://md.research.elamur.ai/free/en/papers/caron-2021-emerging-properties-self-supervised-vision/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Mathilde Caron, Hugo Touvron, Ishan Misra, et al.*2021 · 6,046 citations*
21. **[EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://md.research.elamur.ai/free/en/papers/tan-2019-efficientnet-rethinking-model-scaling-convolutional/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Mingxing Tan, Quoc V. Le*2019 · 5,416 citations*
22. [**WaveNet: A Generative Model for Raw Audio arXiv:1609.03499**Aaron van den Oord, Sander Dieleman, Heiga Zen, et al.*2016 · 5,269 citations*](https://md.research.elamur.ai/free/en/papers/oord-2016-wavenet-generative-model-raw-audio/)
23. [**mixup: Beyond Empirical Risk Minimization arXiv:1710.09412**Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, et al.*2017 · 4,928 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2017-mixup-empirical-risk-minimization/)
24. [**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/)
25. **[Billion-scale similarity search with GPUs](https://md.research.elamur.ai/free/en/papers/johnson-2017-billion-scale-similarity-search-gpus/) [IEEE Transactions on Big Data](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-big-data/)**Jeff Johnson, Matthijs Douze, Hervé Jégou*2017 · 4,728 citations*
26. [**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/)
27. **[XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks](https://md.research.elamur.ai/free/en/papers/rastegari-2016-xnor-net-imagenet-classification-using/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, et al.*2016 · 4,402 citations*
28. [**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/)
29. [**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/)
30. [**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/)
31. **[LXMERT: Learning Cross-Modality Encoder Representations from Transformers](https://md.research.elamur.ai/free/en/papers/tan-2019-lxmert-learning-cross-modality-encoder/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Tan, Mohit Bansal*2019 · 2,789 citations*
32. **[Revisiting Unreasonable Effectiveness of Data in Deep Learning Era](https://md.research.elamur.ai/free/en/papers/sun-2017-revisiting-unreasonable-effectiveness-data-deep/) [IEEE International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-computer-vision-iccv/)**Chen Sun, Abhinav Shrivastava, Saurabh Singh, et al.*2017 · 2,512 citations*
33. **[Self-critical Sequence Training for Image Captioning](https://md.research.elamur.ai/free/en/papers/rennie-2016-self-critical-sequence-training-image/) [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/)**Steven J. Rennie, Etienne Marcheret, Youssef Mroueh, et al.*2016 · 2,404 citations*
34. [**Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) arXiv:1511.07289**Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter*2015 · 2,314 citations*](https://md.research.elamur.ai/free/en/papers/clevert-2015-fast-accurate-deep-network-learning/)
35. [**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/)
36. **[Deep Networks with Stochastic Depth](https://md.research.elamur.ai/free/en/papers/huang-2016-deep-networks-stochastic-depth/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Gao Huang, Yu Sun, Zhuang Liu, et al.*2016 · 2,160 citations*
37. **[Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization](https://md.research.elamur.ai/free/en/papers/narayan-2018-don-t-give-me-details/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shashi Narayan, Shay B. Cohen, Mirella Lapata*2018 · 2,149 citations*
38. **[Designing Network Design Spaces](https://md.research.elamur.ai/free/en/papers/radosavovic-2020-designing-network-design-spaces/) [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/)**Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, et al.*2020 · 2,040 citations*
39. [**Focal Loss for Dense Object Detection arXiv:1708.02002**Tsung-Yi Lin, Priya Goyal, Ross Girshick, et al.*2017 · 1,995 citations*](https://md.research.elamur.ai/free/en/papers/lin-2017-focal-loss-dense-object-detection/)
40. **[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*
41. [**Towards Deep Learning Models Resistant to Adversarial Attacks arXiv:1706.06083**Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, et al.*2017 · 1,874 citations*](https://md.research.elamur.ai/free/en/papers/madry-2017-towards-deep-learning-models-resistant/)
42. [**Unsupervised Data Augmentation for Consistency Training arXiv:1904.12848**Qizhe Xie, Zihang Dai, Eduard Hovy, et al.*2019 · 1,871 citations*](https://md.research.elamur.ai/free/en/papers/xie-2019-unsupervised-data-augmentation-consistency-training/)
43. [**OPT: Open Pre-trained Transformer Language Models arXiv:2205.01068**Susan Zhang, Stephen Roller, Naman Goyal, et al.*2022 · 1,755 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2022-opt-open-pre-trained-transformer/)
44. [**Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations arXiv:1609.07061**Itay Hubara, Matthieu Courbariaux, Daniel Soudry, et al.*2016 · 1,610 citations*](https://md.research.elamur.ai/free/en/papers/hubara-2016-quantized-neural-networks-training-neural/)
45. [**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/)
46. [**Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer arXiv:1612.03928**Sergey Zagoruyko, Nikos Komodakis*2016 · 1,542 citations*](https://md.research.elamur.ai/free/en/papers/zagoruyko-2016-paying-more-attention-attention-improving/)
47. [**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/)
48. **[AMC: AutoML for Model Compression and Acceleration on Mobile Devices](https://md.research.elamur.ai/free/en/papers/he-2018-amc-automl-model-compression-acceleration/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yihui He; Ji Lin; Zhijian Liu; Hanrui Wang; Li-Jia Li;, Song Han*2018 · 1,444 citations*
49. **[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*
50. **[FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search](https://md.research.elamur.ai/free/en/papers/wu-2018-fbnet-hardware-aware-efficient-convnet/) [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/)**Bichen Wu, Xiaoliang Dai, Peizhao Zhang, et al.*2018 · 1,405 citations*
51. [**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/)
52. [**Language Modeling with Gated Convolutional Networks arXiv:1612.08083**Yann N. Dauphin, Angela Fan, Michael Auli, et al.*2016 · 1,346 citations*](https://md.research.elamur.ai/free/en/papers/dauphin-2016-language-modeling-gated-convolutional-networks/)
53. **[Habitat: A Platform for Embodied AI Research](https://md.research.elamur.ai/free/en/papers/savva-2019-habitat-platform-embodied-ai-research/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Manolis Savva, Abhishek Kadian, Oleksandr Maksymets, et al.*2019 · 1,313 citations*
54. **[A Primer on Neural Network Models for Natural Language Processing](https://md.research.elamur.ai/free/en/papers/goldberg-2015-primer-neural-network-models-natural/) [Journal of Artificial Intelligence Research](https://md.research.elamur.ai/free/en/venues/journal-of-artificial-intelligence-research/)**Yoav Goldberg*2015 · 1,303 citations*
55. **[Adversarial NLI: A New Benchmark for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/nie-2020-adversarial-nli-new-benchmark-natural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Nie, Adina Williams, Emily Dinan, et al.*2020 · 1,296 citations*
56. [**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/)
57. **[Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering](https://md.research.elamur.ai/free/en/papers/goyal-2016-making-v-vqa-matter-elevating/) [International Journal of Computer Vision](https://md.research.elamur.ai/free/en/venues/international-journal-of-computer-vision/)**Yash Goyal, Tejas Khot, Douglas Summers-Stay, et al.*2016 · 1,281 citations*
58. **[Modeling Context in Referring Expressions](https://md.research.elamur.ai/free/en/papers/yu-2016-modeling-context-referring-expressions/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Licheng Yu, Patrick Poirson, Shan Yang, et al.*2016 · 1,203 citations*
59. **[EIE: Efficient Inference Engine on Compressed Deep Neural Network](https://md.research.elamur.ai/free/en/papers/han-2016-eie-efficient-inference-engine-compressed/) [ACM/IEEE International Symposium on Computer Architecture (ISCA)](https://md.research.elamur.ai/free/en/venues/acm-ieee-international-symposium-on-computer-architecture-isca/)**Song Han, Xingyu Liu, Huizi Mao, et al.*2016 · 1,193 citations*
60. [**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/)
61. [**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/)
62. **[Very Deep Convolutional Networks for Text Classification](https://md.research.elamur.ai/free/en/papers/conneau-2017-very-deep-convolutional-networks-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Alexis Conneau, Holger Schwenk, Loïc Barrault, et al.*2017 · 1,094 citations*
63. **[Vision-Language Models for Vision Tasks: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-vision-language-models-vision-tasks/) [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-pattern-analysis-and-machine-intelligence/)**Jingyi Zhang, Jiaxing Huang, Sheng Jin, et al.*2023 · 1,047 citations*
64. **[MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices](https://md.research.elamur.ai/free/en/papers/sun-2020-mobilebert-compact-task-agnostic-bert/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiqing Sun, Hongkun Yu, Xiaodan Song, et al.*2020 · 1,016 citations*
65. [**U-Net: Convolutional Networks for Biomedical Image Segmentation arXiv:1505.04597**Olaf Ronneberger, Philipp Fischer, Thomas Brox*2015 · 997 citations*](https://md.research.elamur.ai/free/en/papers/ronneberger-2015-u-net-convolutional-networks-biomedical/)
66. [**Generating Long Sequences with Sparse Transformers arXiv:1904.10509**Rewon Child, Scott Gray, Alec Radford, et al.*2019 · 967 citations*](https://md.research.elamur.ai/free/en/papers/child-2019-generating-long-sequences-sparse-transformers/)
67. [**QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding arXiv:1610.02132**Dan Alistarh, Demjan Grubic, Jerry Li, et al.*2016 · 962 citations*](https://md.research.elamur.ai/free/en/papers/alistarh-2016-qsgd-communication-efficient-sgd-gradient/)
68. [**Segment Anything arXiv:2304.02643**Alexander Kirillov, Eric Mintun, Nikhila Ravi, et al.*2023 · 960 citations*](https://md.research.elamur.ai/free/en/papers/kirillov-2023-segment-anything/)
69. [**End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF arXiv:1603.01354**Xuezhe Ma, Eduard Hovy*2016 · 868 citations*](https://md.research.elamur.ai/free/en/papers/ma-2016-end-end-sequence-labeling-bi/)
70. [**DocVQA: A Dataset for VQA on Document Images arXiv:2007.00398**Minesh Mathew, Dimosthenis Karatzas, C.V. Jawahar*2020 · 844 citations*](https://md.research.elamur.ai/free/en/papers/mathew-2020-docvqa-dataset-vqa-document-images/)
71. **[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*
72. **[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*
73. [**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/)
74. [**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/)
75. [**Feature Pyramid Networks for Object Detection arXiv:1612.03144**Tsung-Yi Lin, Piotr Dollar, Ross Girshick, et al.*2016 · 767 citations*](https://md.research.elamur.ai/free/en/papers/lin-2016-feature-pyramid-networks-object-detection/)
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