---
title: "Who cites Pierre Sermanet — 1,745 papers of our library"
description: "1,745 papers of the Elamur Research library cite the works of Pierre Sermanet, found in their bibliographies · page 1 of 3 · 1–100; the most…"
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---
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# Who cites Pierre Sermanet

2,013 citations of their works from 1,745 papers of our library (of the 149,439 whose bibliographies we read) · 277 with a page here, the most cited first · page 1 of 3 · 1–100 · [← Pierre Sermanet](https://md.research.elamur.ai/free/en/authors/pierre-sermanet/)

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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. [**Dropout: A Simple Way to Prevent Neural Networks from Overfitting JMLR 15(56):1929–1958**Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, et al.*2014 · 34,422 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2014-dropout-simple-way-prevent/)
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. **[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*
5. [**Chain-of-Thought Prompting Elicits Reasoning in Large Language Models arXiv:2201.11903**Jason Wei, Xuezhi Wang, Dale Schuurmans, et al.*2022 · 11,499 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-chain-thought-prompting-elicits-reasoning/)
6. [**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/)
7. [**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/)
8. [**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/)
9. [**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/)
10. [**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/)
11. [**Show, Attend and Tell: Neural Image Caption Generation with Visual Attention arXiv:1502.03044**Kelvin Xu, Jimmy Ba, Ryan Kiros, et al.*2015 · 7,670 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-show-attend-tell-neural-image/)
12. **[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*
13. **[Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations](https://md.research.elamur.ai/free/en/papers/krishna-2016-visual-genome-connecting-language-vision/) [International Journal of Computer Vision](https://md.research.elamur.ai/free/en/venues/international-journal-of-computer-vision/)**Ranjay Krishna, Yuke Zhu, Oliver Groth, et al.*2016 · 5,876 citations*
14. **[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*
15. [**Microsoft COCO: Common Objects in Context arXiv:1405.0312**Tsung-Yi Lin, Michael Maire, Serge Belongie, et al.*2014 · 5,131 citations*](https://md.research.elamur.ai/free/en/papers/lin-2014-microsoft-coco-common-objects-context/)
16. [**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/)
17. **[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*
18. [**Caffe: Convolutional Architecture for Fast Feature Embedding arXiv:1408.5093**Yangqing Jia, Evan Shelhamer, Jeff Donahue, et al.*2014 · 4,209 citations*](https://md.research.elamur.ai/free/en/papers/jia-2014-caffe-convolutional-architecture-fast-feature/)
19. **[Large language models are zero-shot reasoners](https://md.research.elamur.ai/free/en/papers/kojima-2022-large-language-models-zero-shot/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Takeshi Kojima, Shixiang Shane Gu, Machel Reid, et al.*2022 · 3,832 citations*
20. [**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/)
21. **[Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books](https://md.research.elamur.ai/free/en/papers/zhu-2015-aligning-books-movies-towards-story/) [IEEE International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-computer-vision-iccv/)**Yukun Zhu, Ryan Kiros, Richard Zemel, et al.*2015 · 3,083 citations*
22. **[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*
23. [**Visual Instruction Tuning arXiv:2304.08485**Haotian Liu, Chunyuan Li, Qingyang Wu, et al.*2023 · 2,617 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-visual-instruction-tuning/)
24. [**ReAct: Synergizing Reasoning and Acting in Language Models arXiv:2210.03629**Shunyu Yao, Jeffrey Zhao, Dian Yu, et al.*2022 · 2,591 citations*](https://md.research.elamur.ai/free/en/papers/yao-2022-react-synergizing-reasoning-acting-language/)
25. **[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*
26. [**Recurrent Neural Network Regularization arXiv:1409.2329**Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals*2014 · 2,412 citations*](https://md.research.elamur.ai/free/en/papers/zaremba-2014-recurrent-neural-network-regularization/)
27. [**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/)
28. **[Reflexion: Language Agents with Verbal Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/shinn-2023-reflexion-language-agents-verbal-reinforcement/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Noah Shinn, Federico Cassano, Edward Berman, et al.*2023 · 2,271 citations*
29. [**Emergent Abilities of Large Language Models arXiv:2206.07682**Jason Wei, Yi Tay, Rishi Bommasani, et al.*2022 · 2,269 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/)
30. **[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*
31. **[Stacked Attention Networks for Image Question Answering](https://md.research.elamur.ai/free/en/papers/yang-2015-stacked-attention-networks-image-question/) [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/)**Zichao Yang, Xiaodong He, Jianfeng Gao, et al.*2015 · 2,157 citations*
32. [**Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1 arXiv:1602.02830**Matthieu Courbariaux, Itay Hubara, Daniel Soudry, et al.*2016 · 2,143 citations*](https://md.research.elamur.ai/free/en/papers/courbariaux-2016-binarized-neural-networks-training-deep/)
33. **[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*
34. [**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/)
35. [**BinaryConnect: Training Deep Neural Networks with binary weights during propagations arXiv:1511.00363**Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David*2015 · 1,885 citations*](https://md.research.elamur.ai/free/en/papers/courbariaux-2015-binaryconnect-training-deep-neural-networks/)
36. [**Qwen Technical Report arXiv:2309.16609**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,669 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/)
37. **[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*
38. [**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/)
39. [**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/)
40. **[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*
41. [**OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks arXiv:1312.6229**Pierre Sermanet, David Eigen, Xiang Zhang, et al.*2013 · 1,423 citations*](https://md.research.elamur.ai/free/en/papers/sermanet-2013-overfeat-integrated-recognition-localization-detection/)
42. **[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*
43. **[VideoBERT: A Joint Model for Video and Language Representation Learning](https://md.research.elamur.ai/free/en/papers/sun-2019-videobert-joint-model-video-language/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Chen Sun, Austin Myers, Carl Vondrick, et al.*2019 · 1,345 citations*
44. **[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*
45. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
46. [**cuDNN: Efficient Primitives for Deep Learning arXiv 2014 (NVIDIA)**Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, et al.*2014 · 1,240 citations*](https://md.research.elamur.ai/free/en/papers/chetlur-2014-cudnn-efficient-primitives-deep-learning/)
47. [**"Why Should I Trust You?": Explaining the Predictions of Any Classifier arXiv:1602.04938**Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin*2016 · 1,205 citations*](https://md.research.elamur.ai/free/en/papers/ribeiro-2016-why-should-i-trust-explaining/)
48. [**Matching Networks for One Shot Learning arXiv:1606.04080**Oriol Vinyals, Charles Blundell, Timothy Lillicrap, et al.*2016 · 1,197 citations*](https://md.research.elamur.ai/free/en/papers/vinyals-2016-matching-networks-one-shot-learning/)
49. **[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*
50. [**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/)
51. [**MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models arXiv:2304.10592**Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.*2023 · 1,141 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-minigpt-4-enhancing-vision-language/)
52. [**InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning arXiv:2305.06500**Wenliang Dai, Junnan Li, Dongxu Li, et al.*2023 · 1,100 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-instructblip-towards-general-purpose-vision/)
53. **[Effective Use of Word Order for Text Categorization with Convolutional Neural Networks](https://md.research.elamur.ai/free/en/papers/johnson-2015-effective-use-word-order-text/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Rie Johnson, Tong Zhang*2015 · 971 citations*
54. **[Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations](https://md.research.elamur.ai/free/en/papers/kobayashi-2018-contextual-augmentation-data-augmentation-words/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sosuke Kobayashi*2018 · 810 citations*
55. [**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/)
56. **[Learning Distributed Representations of Sentences from Unlabelled Data](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-distributed-representations-sentences-unlabelled/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Felix Hill, Kyunghyun Cho, Anna Korhonen*2016 · 765 citations*
57. [**EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks arXiv:1901.11196**Jason Wei, Kai Zou*2019 · 761 citations*](https://md.research.elamur.ai/free/en/papers/wei-2019-eda-easy-data-augmentation-techniques/)
58. [**ProgPrompt: Generating Situated Robot Task Plans using Large Language Models arXiv:2209.11302**Ishika Singh, Valts Blukis, Arsalan Mousavian, et al.*2022 · 735 citations*](https://md.research.elamur.ai/free/en/papers/singh-2022-progprompt-generating-situated-robot-task/)
59. **[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*
60. [**Show and Tell: A Neural Image Caption Generator arXiv:1411.4555**Oriol Vinyals, Alexander Toshev, Samy Bengio, et al.*2014 · 729 citations*](https://md.research.elamur.ai/free/en/papers/vinyals-2014-show-tell-neural-image-caption/)
61. **[CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society](https://md.research.elamur.ai/free/en/papers/li-2023-camel-communicative-agents-mind/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, et al.*2023 · 706 citations*
62. [**Large Language Models Are Human-Level Prompt Engineers arXiv:2211.01910**Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.*2022 · 701 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-large-language-models-human-level/)
63. [**Highway Networks arXiv:1505.00387**Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber*2015 · 680 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2015-highway-networks/)
64. [**Deep Visual-Semantic Alignments for Generating Image Descriptions arXiv:1412.2306**Andrej Karpathy, Li Fei-Fei*2014 · 608 citations*](https://md.research.elamur.ai/free/en/papers/karpathy-2014-deep-visual-semantic-alignments-generating/)
65. [**The Flan Collection: Designing Data and Methods for Effective Instruction Tuning arXiv:2301.13688**Shayne Longpre, Le Hou, Tu Vu, et al.*2023 · 607 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/)
66. [**ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs arXiv:2307.16789**Yujia Qin, Shihao Liang, Yining Ye, et al.*2023 · 589 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)
67. **[LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models](https://md.research.elamur.ai/free/en/papers/song-2022-llm-planner-few-shot-grounded/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Chan Hee Song, Jiaman Wu, Clayton Washington, et al.*2022 · 574 citations*
68. **[MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/fu-2023-mme-comprehensive-evaluation-benchmark-multimodal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.*2023 · 554 citations*
69. **[Fast and Accurate Entity Recognition with Iterated Dilated Convolutions](https://md.research.elamur.ai/free/en/papers/strubell-2017-fast-accurate-entity-recognition-iterated/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Emma Strubell, Patrick Verga, David Belanger, et al.*2017 · 548 citations*
70. **[Gorilla: Large Language Model Connected with Massive APIs](https://md.research.elamur.ai/free/en/papers/patil-2023-gorilla-large-language-model-connected/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shishir G. Patil, Tianjun Zhang, Xin Wang, et al.*2023 · 546 citations*
71. [**TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation arXiv:2305.00447**Keqin Bao; Jizhi Zhang; Yang Zhang; Wenjie Wang; Fuli Feng;, Xiangnan He*2023 · 531 citations*](https://md.research.elamur.ai/free/en/papers/bao-2023-tallrec-effective-efficient-tuning-framework/)
72. [**Learning Structured Sparsity in Deep Neural Networks arXiv:1608.03665**Wei Wen, Chunpeng Wu, Yandan Wang, et al.*2016 · 530 citations*](https://md.research.elamur.ai/free/en/papers/wen-2016-learning-structured-sparsity-deep-neural/)
73. [**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/)
74. [**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/)
75. [**Language Models are Multilingual Chain-of-Thought Reasoners arXiv:2210.03057**Freda Shi, Mirac Suzgun, Markus Freitag, et al.*2022 · 494 citations*](https://md.research.elamur.ai/free/en/papers/shi-2022-language-models-multilingual-chain-thought/)
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