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Who cites Trevor Jackson Darrell

7,658 citations of their works from 5,295 papers of our library (of the 149,439 whose bibliographies we read) · 445 with a page here, the most cited first · page 1 of 5 · 1–100 · ← Trevor Jackson Darrell

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  1. Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556Karen Simonyan, Andrew Zisserman2014 · 73,393 citations
  2. Rich feature hierarchies for accurate object detection and semantic segmentationIEEE Computer Society Conference on Computer Vision and Pattern RecognitionRoss Girshick, Jeff Donahue, Trevor Darrell, et al.2013 · 31,930 citations
  3. PyTorch: An Imperative Style, High-Performance Deep Learning LibraryarXiv:1912.01703Adam Paszke, Sam Gross, Francisco Massa, et al.2019 · 18,645 citations
  4. Momentum Contrast for Unsupervised Visual Representation LearningIEEE Computer Society Conference on Computer Vision and Pattern RecognitionKaiming He, Haoqi Fan, Yuxin Wu, et al.2019 · 13,302 citations
  5. TensorFlow: A system for large-scale machine learningarXiv:1605.08695Martin Abadi, Paul Barham, Jianmin Chen, et al.2016 · 12,711 citations
  6. Exploring the Limits of Transfer Learning with a Unified Text-to-Text TransformerarXiv:1910.10683Colin Raffel, Noam Shazeer, Adam Roberts, et al.2019 · 11,325 citations
  7. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision ApplicationsarXiv:1704.04861Andrew G. Howard, Menglong Zhu, Bo Chen, et al.2017 · 9,729 citations
  8. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed SystemsarXiv:1603.04467Martín Abadi, Ashish Agarwal, Paul Barham, et al.2016 · 9,512 citations
  9. Deep Residual Learning for Image RecognitionarXiv:1512.03385Kaiming He, Xiangyu Zhang, Shaoqing Ren, et al.2015 · 9,425 citations
  10. Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020Alec Radford, Jong Wook Kim, Chris Hallacy, et al.2021 · 8,767 citations
  11. A Simple Framework for Contrastive Learning of Visual RepresentationsarXiv:2002.05709Ting Chen, Simon Kornblith, Mohammad Norouzi, et al.2020 · 8,000 citations
  12. Show, Attend and Tell: Neural Image Caption Generation with Visual AttentionarXiv:1502.03044Kelvin Xu, Jimmy Ba, Ryan Kiros, et al.2015 · 7,670 citations
  13. Representation Learning with Contrastive Predictive CodingarXiv:1807.03748Aaron van den Oord, Yazhe Li, Oriol Vinyals2018 · 7,022 citations
  14. Learning Transferable Architectures for Scalable Image RecognitionIEEE Computer Society Conference on Computer Vision and Pattern RecognitionBarret Zoph, Vijay Vasudevan, Jonathon Shlens, et al.2017 · 6,583 citations
  15. Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksarXiv:1703.03400Chelsea Finn, Pieter Abbeel, Sergey Levine2017 · 6,549 citations
  16. Grad-CAM: Visual Explanations from Deep Networks via Gradient-based LocalizationInternational Journal of Computer VisionRamprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, et al.2016 · 6,394 citations
  17. Intriguing properties of neural networksarXiv:1312.6199Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, et al.2013 · 5,999 citations
  18. Survey of Hallucination in Natural Language GenerationACM Computing SurveysZiwei Ji, Nayeon Lee, Rita Frieske, et al.2022 · 5,974 citations
  19. Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image AnnotationsInternational Journal of Computer VisionRanjay Krishna, Yuke Zhu, Oliver Groth, et al.2016 · 5,876 citations
  20. A Broad-Coverage Challenge Corpus for Sentence Understanding through InferenceConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Adina Williams, Nikita Nangia, Samuel R. Bowman2018 · 5,551 citations
  21. Microsoft COCO: Common Objects in ContextarXiv:1405.0312Tsung-Yi Lin, Michael Maire, Serge Belongie, et al.2014 · 5,131 citations
  22. Neural Architecture Search with Reinforcement LearningarXiv:1611.01578Barret Zoph, Quoc V. Le2016 · 4,413 citations
  23. Caffe: Convolutional Architecture for Fast Feature EmbeddingarXiv:1408.5093Yangqing Jia, Evan Shelhamer, Jeff Donahue, et al.2014 · 4,209 citations
  24. Abstractive Text Summarization using Sequence-to-sequence RNNs and BeyondConference on Computational Natural Language Learning (CoNLL)Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, et al.2016 · 3,260 citations
  25. Continual Lifelong Learning with Neural Networks: A ReviewarXiv:1802.07569German I. Parisi, Ronald Kemker, Jose L. Part, et al.2018 · 3,224 citations
  26. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  27. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  28. What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?arXiv:1703.04977Alex Kendall, Yarin Gal2017 · 2,870 citations
  29. LXMERT: Learning Cross-Modality Encoder Representations from TransformersConference on Empirical Methods in Natural Language Processing (EMNLP)Hao Tan, Mohit Bansal2019 · 2,789 citations
  30. Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingarXiv:2205.11487Chitwan Saharia, William Chan, Saurabh Saxena, et al.2022 · 2,533 citations
  31. Generating Sentences from a Continuous SpaceConference on Computational Natural Language Learning (CoNLL)Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al.2016 · 2,435 citations
  32. UNITER: UNiversal Image-TExt Representation LearningLecture notes in computer scienceYen-Chun Chen, Linjie Li, Licheng Yu, et al.2019 · 2,418 citations
  33. Embedding Entities and Relations for Learning and Inference in Knowledge BasesarXiv:1412.6575Bishan Yang, Wen-tau Yih, Xiaodong He, et al.2014 · 2,370 citations
  34. Relational inductive biases, deep learning, and graph networksarXiv:1806.01261Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.2018 · 2,335 citations
  35. GPT-4o System CardarXiv:2410.21276OpenAI, Aaron Hurst, Adam Lerer, et al.2024 · 2,304 citations
  36. ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language TasksarXiv:1908.02265Jiasen Lu, Dhruv Batra, Devi Parikh, et al.2019 · 2,302 citations
  37. Flamingo: a Visual Language Model for Few-Shot LearningarXiv:2204.14198Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.2022 · 2,246 citations
  38. Tensor Fusion Network for Multimodal Sentiment AnalysisConference on Empirical Methods in Natural Language Processing (EMNLP)Amir Zadeh, Minghai Chen, Soujanya Poria, et al.2017 · 2,125 citations
  39. GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question AnsweringIEEE Computer Society Conference on Computer Vision and Pattern RecognitionDrew A. Hudson, Christopher D. Manning2019 · 2,078 citations
  40. MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed SystemsarXiv:1512.01274Tianqi Chen, Mu Li, Yutian Li, et al.2015 · 2,000 citations
  41. Focal Loss for Dense Object DetectionarXiv:1708.02002Tsung-Yi Lin, Priya Goyal, Ross Girshick, et al.2017 · 1,995 citations
  42. Bidirectional Attention Flow for Machine ComprehensionarXiv:1611.01603Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, et al.2016 · 1,988 citations
  43. Microsoft COCO Captions: Data Collection and Evaluation ServerarXiv:1504.00325Xinlei Chen, Hao Fang, Tsung-Yi Lin, et al.2015 · 1,948 citations
  44. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
  45. Language (Technology) is Power: A Critical Survey of “Bias” in NLPAnnual Meeting of the Association for Computational Linguistics (ACL)Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.2020 · 1,716 citations
  46. Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A SurveyACM Computing SurveysBonan Min, Hayley Ross, Elior Sulem, et al.2021 · 1,556 citations
  47. CLIPScore: A Reference-free Evaluation Metric for Image CaptioningConference on Empirical Methods in Natural Language Processing (EMNLP)Jack Hessel, Ari Holtzman, Maxwell Forbes, et al.2021 · 1,550 citations
  48. Understanding Black-box Predictions via Influence FunctionsarXiv:1703.04730Pang Wei Koh, Percy Liang2017 · 1,514 citations
  49. DINOv2: Learning Robust Visual Features without SupervisionarXiv:2304.07193Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.2023 · 1,513 citations
  50. LAION-5B: An open large-scale dataset for training next generation image-text modelsarXiv:2210.08402Christoph Schuhmann, Romain Beaumont, Richard Vencu, et al.2022 · 1,485 citations
  51. Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environmentsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionPeter Anderson, Qi Wu, Damien Teney, et al.2017 · 1,414 citations
  52. Generation and Comprehension of Unambiguous Object DescriptionsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJunhua Mao, Jonathan Huang, Alexander Toshev, et al.2015 · 1,388 citations
  53. Unifying Visual-Semantic Embeddings with Multimodal Neural Language ModelsarXiv:1411.2539Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel2014 · 1,371 citations
  54. ReferItGame: Referring to Objects in Photographs of Natural ScenesConference on Empirical Methods in Natural Language Processing (EMNLP)Sahar Kazemzadeh, Vicente Ordonez, Mark Matten, et al.2014 · 1,317 citations
  55. Long Short-Term Memory-Networks for Machine ReadingConference on Empirical Methods in Natural Language Processing (EMNLP)Jianpeng Cheng, Li Dong, Mirella Lapata2016 · 1,313 citations
  56. Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question AnsweringInternational Journal of Computer VisionYash Goyal, Tejas Khot, Douglas Summers-Stay, et al.2016 · 1,281 citations
  57. The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
  58. Modeling Context in Referring ExpressionsLecture notes in computer scienceLicheng Yu, Patrick Poirson, Shan Yang, et al.2016 · 1,203 citations
  59. Matching Networks for One Shot LearningarXiv:1606.04080Oriol Vinyals, Charles Blundell, Timothy Lillicrap, et al.2016 · 1,197 citations
  60. Efficient Low-rank Multimodal Fusion With Modality-Specific FactorsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhun Liu, Ying Shen, Varun Bharadhwaj Lakshminarasimhan, et al.2018 · 1,188 citations
  61. MASS: Masked Sequence to Sequence Pre-training for Language GenerationarXiv:1905.02450Kaitao Song, Xu Tan, Tao Qin, et al.2019 · 1,143 citations
  62. MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language ModelsarXiv:2304.10592Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.2023 · 1,141 citations
  63. Neural Module NetworksIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJacob Andreas, Marcus Rohrbach, Trevor Darrell, et al.2015 · 1,140 citations
  64. VL-BERT: Pre-training of Generic Visual-Linguistic RepresentationsarXiv:1908.08530Weijie Su, Xizhou Zhu, Yue Cao, et al.2019 · 1,066 citations
  65. Privacy Risk in Machine Learning: Analyzing the Connection to OverfittingarXiv:1709.01604Samuel Yeom, Irene Giacomelli, Matt Fredrikson, et al.2017 · 1,036 citations
  66. BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply ChainarXiv:1708.06733Tianyu Gu, Brendan Dolan-Gavitt, Siddharth Garg2017 · 1,024 citations
  67. Evaluating Object Hallucination in Large Vision-Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Yifan Li, Yifan Du, Kun Zhou, et al.2023 · 1,004 citations
  68. PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 1,000 citations
  69. U-Net: Convolutional Networks for Biomedical Image SegmentationarXiv:1505.04597Olaf Ronneberger, Philipp Fischer, Thomas Brox2015 · 997 citations
  70. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
  71. Segment AnythingarXiv:2304.02643Alexander Kirillov, Eric Mintun, Nikhila Ravi, et al.2023 · 960 citations
  72. Visualizing and Understanding Recurrent NetworksarXiv:1506.02078Andrej Karpathy, Justin Johnson, Li Fei-Fei2015 · 954 citations
  73. Visual7W: Grounded Question Answering in ImagesIEEE Computer Society Conference on Computer Vision and Pattern RecognitionYuke Zhu, Oliver Groth, Michael Bernstein, et al.2015 · 952 citations
  74. PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph CompilationASPLOS 2024Jason Ansel, Edward Yang, Horace He, et al.2024 · 946 citations
  75. Visualizing and Understanding Neural Models in NLPConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jiwei Li, Xinlei Chen, Eduard Hovy, et al.2016 · 855 citations
  76. DocVQA: A Dataset for VQA on Document ImagesarXiv:2007.00398Minesh Mathew, Dimosthenis Karatzas, C.V. Jawahar2020 · 844 citations
  77. CIDEr: Consensus-based Image Description EvaluationarXiv:1411.5726Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh2014 · 827 citations
  78. Ask Me Anything: Dynamic Memory Networks for Natural Language ProcessingarXiv:1506.07285Ankit Kumar, Ozan Irsoy, Peter Ondruska, et al.2015 · 801 citations
  79. Visualizing and Understanding Convolutional NetworksarXiv:1311.2901Matthew D Zeiler, Rob Fergus2013 · 771 citations
  80. ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday TasksIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMohit Shridhar; Jesse Thomason; Daniel Gordon; Yonatan Bisk; Winson Han; Roozbeh Mottaghi; Luke Zettlemoyer;, Dieter Fox2019 · 765 citations
  81. AdapterHub: A Framework for Adapting TransformersConference on Empirical Methods in Natural Language Processing (EMNLP)Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, et al.2020 · 754 citations
  82. Analysis Methods in Neural Language Processing: A SurveyTransactions of the Association for Computational Linguistics (TACL)Yonatan Belinkov, James Glass2019 · 740 citations
  83. Dice Loss for Data-imbalanced NLP TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoya Li, Xiaofei Sun, Yuxian Meng, et al.2020 · 735 citations
  84. Adversarial Multi-task Learning for Text ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Pengfei Liu, Xipeng Qiu, Xuanjing Huang2017 · 729 citations
  85. Show and Tell: A Neural Image Caption GeneratorarXiv:1411.4555Oriol Vinyals, Alexander Toshev, Samy Bengio, et al.2014 · 729 citations
  86. Mitigating Gender Bias in Natural Language Processing: Literature ReviewAnnual Meeting of the Association for Computational Linguistics (ACL)Tony Sun, Andrew Gaut, Shirlyn Tang, et al.2019 · 724 citations
  87. Crosslingual Generalization through Multitask FinetuningarXiv:2211.01786Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.2022 · 703 citations
  88. Learning multiple visual domains with residual adaptersarXiv:1705.08045Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi2017 · 694 citations
  89. TVQA: Localized, Compositional Video Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Jie Lei, Licheng Yu, Mohit Bansal, et al.2018 · 687 citations
  90. A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)Alane Suhr, Stephanie Zhou, Ally Zhang, et al.2019 · 670 citations
  91. CoCa: Contrastive Captioners are Image-Text Foundation ModelsarXiv:2205.01917Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.2022 · 667 citations
  92. A simple neural network module for relational reasoningarXiv:1706.01427Adam Santoro, David Raposo, David G. T. Barrett, et al.2017 · 632 citations
  93. Object Hallucination in Image CaptioningConference on Empirical Methods in Natural Language Processing (EMNLP)Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, et al.2018 · 626 citations
  94. e-SNLI: Natural Language Inference with Natural Language ExplanationsarXiv:1812.01193Oana-Maria Camburu, Tim Rocktäschel, Thomas Lukasiewicz, et al.2018 · 622 citations
  95. Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasmConference on Empirical Methods in Natural Language Processing (EMNLP)Bjarke Felbo, Alan Mislove, Anders Søgaard, et al.2017 · 621 citations
  96. Deep Visual-Semantic Alignments for Generating Image DescriptionsarXiv:1412.2306Andrej Karpathy, Li Fei-Fei2014 · 608 citations
  97. Masked Autoencoders Are Scalable Vision LearnersarXiv:2111.06377Kaiming He, Xinlei Chen, Saining Xie, et al.2021 · 596 citations
  98. An efficient framework for learning sentence representationsarXiv:1803.02893Lajanugen Logeswaran, Honglak Lee2018 · 577 citations
  99. Learning to Compose Neural Networks for Question AnsweringConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jacob Andreas, Marcus Rohrbach, Trevor Darrell, et al.2016 · 573 citations
  100. Reducing Transformer Depth on Demand with Structured DropoutarXiv:1909.11556Angela Fan, Edouard Grave, Armand Joulin2019 · 560 citations

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