---
title: "Who cites Laurens van der Maaten — 1,302 papers of our library"
description: "1,302 papers of the Elamur Research library cite the works of Laurens van der Maaten, found in their bibliographies · page 1 of 2 · 1–100; the…"
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---
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# Who cites Laurens van der Maaten

1,404 citations of their works from 1,302 papers of our library (of the 149,439 whose bibliographies we read) · 135 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Laurens van der Maaten](https://md.research.elamur.ai/free/en/authors/laurens-van-der-maaten/)

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1. **[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*
2. [**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/)
3. **[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*
4. [**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/)
5. [**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/)
6. [**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/)
7. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
8. **[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*
9. **[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*
10. [**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/)
11. [**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/)
12. [**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/)
13. [**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/)
14. [**Robust Speech Recognition via Large-Scale Weak Supervision arXiv:2212.04356**Alec Radford, Jong Wook Kim, Tao Xu, et al.*2022 · 2,546 citations*](https://md.research.elamur.ai/free/en/papers/radford-2022-robust-speech-recognition-large-scale/)
15. **[GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering](https://md.research.elamur.ai/free/en/papers/hudson-2019-gqa-new-dataset-real-world/) [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/)**Drew A. Hudson, Christopher D. Manning*2019 · 2,078 citations*
16. **[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*
17. [**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/)
18. **[Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision](https://md.research.elamur.ai/free/en/papers/jia-2021-scaling-up-visual-vision-language/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Chao Jia, Yinfei Yang, Ye Xia, et al.*2021 · 1,615 citations*
19. [**DINOv2: Learning Robust Visual Features without Supervision arXiv:2304.07193**Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.*2023 · 1,513 citations*](https://md.research.elamur.ai/free/en/papers/oquab-2023-dinov2-learning-robust-visual-features/)
20. [**LAION-5B: An open large-scale dataset for training next generation image-text models arXiv:2210.08402**Christoph Schuhmann, Romain Beaumont, Richard Vencu, et al.*2022 · 1,485 citations*](https://md.research.elamur.ai/free/en/papers/schuhmann-2022-laion-5b-open-large-scale/)
21. [**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/)
22. **[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*
23. [**Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges arXiv:2103.11251 · Statistics Surveys, 2021**Cynthia Rudin; Chaofan Chen; Zhi Chen; Haiyang Huang; Lesia Semenova;, Chudi Zhong*2021 · 974 citations*](https://md.research.elamur.ai/free/en/papers/rudin-2021-interpretable-machine-learning-fundamental/)
24. **[ImageBind: One Embedding Space To Bind Them All](https://md.research.elamur.ai/free/en/papers/girdhar-2023-imagebind-one-embedding-space-bind/) [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/)**Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, et al.*2023 · 954 citations*
25. **[MMBench: Is Your Multi-modal Model an All-around Player?](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yuan Liu, Haodong Duan, Yuanhan Zhang, et al.*2023 · 942 citations*
26. [**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/)
27. **[Progressive Differentiable Architecture Search: Bridging the Depth Gap between Search and Evaluation](https://md.research.elamur.ai/free/en/papers/chen-2019-progressive-differentiable-architecture-search-bridging/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Xin Chen, Lingxi Xie, Jun Wu, et al.*2019 · 732 citations*
28. [**Efficient Neural Architecture Search via Parameter Sharing arXiv:1802.03268**Hieu Pham, Melody Y. Guan, Barret Zoph, et al.*2018 · 699 citations*](https://md.research.elamur.ai/free/en/papers/pham-2018-efficient-neural-architecture-search-parameter/)
29. **[TVQA: Localized, Compositional Video Question Answering](https://md.research.elamur.ai/free/en/papers/lei-2018-tvqa-localized-compositional-video-question/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jie Lei, Licheng Yu, Mohit Bansal, et al.*2018 · 687 citations*
30. [**A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)**Alane Suhr, Stephanie Zhou, Ally Zhang, et al.*2019 · 670 citations*](https://md.research.elamur.ai/free/en/papers/suhr-2019-corpus-reasoning-natural-language-grounded/)
31. [**CoCa: Contrastive Captioners are Image-Text Foundation Models arXiv:2205.01917**Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.*2022 · 667 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-coca-contrastive-captioners-image-text/)
32. [**A simple neural network module for relational reasoning arXiv:1706.01427**Adam Santoro, David Raposo, David G. T. Barrett, et al.*2017 · 632 citations*](https://md.research.elamur.ai/free/en/papers/santoro-2017-simple-neural-network-module-relational/)
33. **[Attention Guided Graph Convolutional Networks for Relation Extraction](https://md.research.elamur.ai/free/en/papers/guo-2019-attention-guided-graph-convolutional-networks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhijiang Guo, Yan Zhang, Wei Lu*2019 · 602 citations*
34. **[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*
35. **[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*
36. **[Inferring and Executing Programs for Visual Reasoning](https://md.research.elamur.ai/free/en/papers/johnson-2017-inferring-executing-programs-visual-reasoning/) [IEEE International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-computer-vision-iccv/)**Justin Johnson, Bharath Hariharan, Laurens van der Maaten, et al.*2017 · 557 citations*
37. **[A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge](https://md.research.elamur.ai/free/en/papers/schwenk-2022-okvqa-benchmark-visual-question-answering/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, et al.*2022 · 509 citations*
38. [**Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time arXiv:2203.05482**Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, et al.*2022 · 507 citations*](https://md.research.elamur.ai/free/en/papers/wortsman-2022-model-soups-averaging-weights-multiple/)
39. [**Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model arXiv:2401.09417**Lianghui Zhu, Bencheng Liao, Qian Zhang, et al.*2024 · 500 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2024-vision-mamba-efficient-visual-representation/)
40. [**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/)
41. [**ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware arXiv:1812.00332**Han Cai, Ligeng Zhu, Song Han*2018 · 479 citations*](https://md.research.elamur.ai/free/en/papers/cai-2018-proxylessnas-direct-neural-architecture-search/)
42. [**LLaVA-OneVision: Easy Visual Task Transfer arXiv:2408.03326**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 477 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
43. **[MVBench: A Comprehensive Multi-modal Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/li-2023-mvbench-comprehensive-multi-modal-video/) [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/)**Kunchang Li, Yali Wang, Yinan He, et al.*2023 · 463 citations*
44. [**FreeLB: Enhanced Adversarial Training for Natural Language Understanding arXiv:1909.11764**Chen Zhu, Yu Cheng, Zhe Gan, et al.*2019 · 452 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2019-freelb-enhanced-adversarial-training-natural/)
45. **[Experience Grounds Language](https://md.research.elamur.ai/free/en/papers/bisk-2020-experience-grounds-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yonatan Bisk, Ari Holtzman, Jesse Thomason, et al.*2020 · 439 citations*
46. [**Benchmarking Neural Network Robustness to Common Corruptions and Perturbations arXiv:1903.12261**Dan Hendrycks, Thomas Dietterich*2019 · 434 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2019-benchmarking-neural-network-robustness-common/)
47. [**The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes arXiv:2005.04790**Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.*2020 · 420 citations*](https://md.research.elamur.ai/free/en/papers/kiela-2020-hateful-memes-challenge-detecting-hate/)
48. [**Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding arXiv:1810.02338**Kexin Yi, Jiajun Wu, Chuang Gan, et al.*2018 · 407 citations*](https://md.research.elamur.ai/free/en/papers/yi-2018-neural-symbolic-vqa-disentangling-reasoning/)
49. **[ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering](https://md.research.elamur.ai/free/en/papers/yu-2019-activitynet-qa-dataset-understanding-complex/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Zhou Yu, Dejing Xu, Jun Yu, et al.*2019 · 403 citations*
50. **[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*
51. [**FiLM: Visual Reasoning with a General Conditioning Layer arXiv:1709.07871**Ethan Perez, Florian Strub, Harm de Vries, et al.*2017 · 400 citations*](https://md.research.elamur.ai/free/en/papers/perez-2017-film-visual-reasoning-general-conditioning/)
52. [**Green AI arXiv:1907.10597**Roy Schwartz, Jesse Dodge, Noah A. Smith, et al.*2019 · 389 citations*](https://md.research.elamur.ai/free/en/papers/schwartz-2019-green-ai/)
53. **[ViperGPT: Visual Inference via Python Execution for Reasoning](https://md.research.elamur.ai/free/en/papers/suris-2023-vipergpt-visual-inference-python-execution/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Didac Suris, Sachit Menon, Carl Vondrick*2023 · 383 citations*
54. [**PaLI: A Jointly-Scaled Multilingual Language-Image Model arXiv:2209.06794**Xi Chen, Xiao Wang, Soravit Changpinyo, et al.*2022 · 371 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-pali-jointly-scaled-multilingual-language/)
55. [**Averaging Weights Leads to Wider Optima and Better Generalization arXiv:1803.05407**Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, et al.*2018 · 366 citations*](https://md.research.elamur.ai/free/en/papers/izmailov-2018-averaging-weights-leads-wider-optima/)
56. **[Visual Programming: Compositional visual reasoning without training](https://md.research.elamur.ai/free/en/papers/gupta-2022-visual-programming-compositional-visual-reasoning/) [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/)**Tanmay Gupta, Aniruddha Kembhavi*2022 · 347 citations*
57. **[Neural Paraphrase Generation with Stacked Residual LSTM Networks](https://md.research.elamur.ai/free/en/papers/prakash-2016-neural-paraphrase-generation-stacked-residual/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Aaditya Prakash, Sadid A. Hasan, Kathy Lee, et al.*2016 · 337 citations*
58. [**Discovering Language Model Behaviors with Model-Written Evaluations arXiv:2212.09251**Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.*2022 · 328 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-discovering-language-model-behaviors-model/)
59. **[Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2023-chameleon-plug-play-compositional-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Pan Lu, Baolin Peng, Hao Cheng, et al.*2023 · 327 citations*
60. [**ALFWorld: Aligning Text and Embodied Environments for Interactive Learning arXiv:2010.03768**Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, et al.*2020 · 322 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2020-alfworld-aligning-text-embodied-environments/)
61. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) arXiv:2309.17421**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
62. **[CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/le-2022-coderl-mastering-code-generation-through/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hung Le, Yue Wang, Akhilesh Deepak Gotmare, et al.*2022 · 297 citations*
63. **[SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2018-switchout-efficient-data-augmentation-algorithm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xinyi Wang, Hieu Pham, Zihang Dai, et al.*2018 · 290 citations*
64. [**Beyond Data and Model Parallelism for Deep Neural Networks SysML 2019**Zhihao Jia, Matei Zaharia, Alex Aiken*2018 · 280 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-beyond-data-model-parallelism-deep/)
65. [**Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis ACM Computing Surveys 2019**Tal Ben-Nun, Torsten Hoefler*2018 · 275 citations*](https://md.research.elamur.ai/free/en/papers/nun-2018-demystifying-parallel-distributed-deep-learning/)
66. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone arXiv:2408.01800**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
67. **[Mapping Instructions and Visual Observations to Actions with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/misra-2017-mapping-instructions-visual-observations-actions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dipendra Misra, John Langford, Yoav Artzi*2017 · 255 citations*
68. [**Once-for-All: Train One Network and Specialize it for Efficient Deployment arXiv:1908.09791**Han Cai, Chuang Gan, Tianzhe Wang, et al.*2019 · 252 citations*](https://md.research.elamur.ai/free/en/papers/cai-2019-once-all-train-one-network/)
69. [**Improved Knowledge Distillation via Teacher Assistant arXiv:1902.03393**Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, et al.*2019 · 248 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2019-improved-knowledge-distillation-teacher-assistant/)
70. [**The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision arXiv:1904.12584**Jiayuan Mao, Chuang Gan, Pushmeet Kohli, et al.*2019 · 241 citations*](https://md.research.elamur.ai/free/en/papers/mao-2019-neuro-symbolic-concept-learner-interpreting/)
71. [**FigureQA: An Annotated Figure Dataset for Visual Reasoning arXiv:1710.07300**Samira Ebrahimi Kahou, Vincent Michalski, Adam Atkinson, et al.*2017 · 240 citations*](https://md.research.elamur.ai/free/en/papers/kahou-2017-figureqa-annotated-figure-dataset-visual/)
72. **[Beyond neural scaling laws: beating power law scaling via data pruning](https://md.research.elamur.ai/free/en/papers/sorscher-2022-neural-scaling-laws-beating-power/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ben Sorscher, Robert Geirhos, Shashank Shekhar, et al.*2022 · 231 citations*
73. **[A Survey of Reinforcement Learning Informed by Natural Language](https://md.research.elamur.ai/free/en/papers/luketina-2019-survey-reinforcement-learning-informed-natural/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Jelena Luketina, Nantas Nardelli, Gregory Farquhar, et al.*2019 · 231 citations*
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