注意：当前的评估报告仅用于征求意见的目的。团队诚挚地请求您宝贵的反馈和建议。我们致力于根据现有证据持续修订报告。

背景

自1950年图灵测试提出以来，到2022年ChatGPT解决图灵测试，人工智能（AI）经历了数十年的蓬勃发展。在这持续演进的过程中，许多有影响力的人物、概念、事件和成就涌现出来，进一步诞生了众多AI的子领域和研究课题。这些成就丰富了AI生态系统，使其能够处理单一任务，如图像分类，增强复杂的应用场景，如互联网服务，甚至实现像人类一样的通用智能。

评估标准

我们筛选出对发展人工智能及相关领域和学科具有巨大影响和显著推动作用的顶尖人工智能成果（时间从2022年到2023年）。我们的评估标准如下：

  • 人工智能或其子领域的原创或开创性工作。
  • 将对人工智能或其子领域发展具有重大推动作用的工作。
  • 被工业界或学术界广泛使用或引用的工作。

人工智能杰出成果（2022-2023）

人工智能杰出成果概览

（请注意树状图可以放大、缩小和移动；可以点击分支处的圆圈来展开或折叠图的内容。）

人工智能杰出成果详情

在考虑主要贡献者时，我们仅列出第一作者和通讯作者，包括同等贡献的作者，如果没有通讯作者则列出最后作者。如果您对列表有任何意见或建议，请发送邮件至： 发送电子邮件至 benchcouncil.evaluation@gmail.com

领域 工作 出版物 引用 主要贡献者 机构 国家
Vision Swin Transformer V2 Swin Transformer V2: Scaling Up Capacity and Resolution 769 Ze Liu, Han Hu Microsoft Research Asia China
Simmim Simmim: A simple framework for masked image modeling 652 Zhenda Xie, Zheng Zhang, Yue Cao, Han Hu Tsinghua University, Microsoft Research Asia, Xi'an Jiaotong University China
Scaling ViT Scaling vision transformers 630 Xiaohua Zhai, Alexander Kolesnikov,Lucas Beyer Google Switzerland
RepLKNet Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs 392 Xiaohan Ding,Xiangyu Zhang BNRist, Tsinghua University, MEGVII, Aberystwyth University China, UK
LocalViT Localvit: Bringing locality to vision transformers 363 Yawei Li, Luc Van Gool ETH Zurich, KU Leuven Switzerland, Belgium
LaMa Resolution-robust Large Mask Inpainting with Fourier Convolutions 305 Roman Suvorov, Victor Lempitsky Samsung, EPFL, Skolkovo Institute of Science and Technology Russia, Switzerland, Korea
Instructpix2pix Instructpix2pix: Learning to follow image editing instructions 246 Tim Brooks, Aleksander Holynski, Alexei A. Efros UC Berkeley USA
ConvNeXts A ConvNet for the 2020s 2508 Zhuang Liu, Saining Xie Facebook, UC Berkeley USA
ConvMixer Patches Are All You Need? 247 Asher Trockman, J. Zico Kolter CMU, Bosch Center for AI USA
CMT CMT: Convolutional Neural Networks Meet Vision Transformers 361 Jianyuan Guo, Yunhe Wang, Chang Xu University of Sydney, Huawei Australia, China
Block-NeRF Block-NeRF: Scalable Large Scene Neural View Synthesis 279 Matthew Tancik, Henrik Kretzschmar UC Berkeley, Waymo, Google USA
BEVFormer BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers 383 Zhiqi Li, Wenhai Wang, Hongyang Li, Jifeng Dai Nanjing University, Shanghai AI Lab, The University of Hong Kong China
Prompt-to-Prompt Prompt-to-prompt image editing with cross attention control 328 Amir Hertz, Daniel Cohen-Or Google, Tel Aviv University USA, Israel
TensoRF TensoRF: Tensorial Radiance Fields 372 Anpei Chen, Zexiang Xu, Hao Su ShanghaiTech University, Adobe, University of Tubingen, UC San Diego China, USA, Germany
AlterNet How Do Vision Transformers Work? 288 Namuk Park, Songkuk Kim Yonsei University, NAVER AI Lab Korea
VPT Visual Prompt Tuning 455 Menglin Jia, Luming Tang, Ser-Nam Lim Cornell University, Meta, University of Copenhagen USA, Denmark
VAN Visual attention network 273 Meng-Hao Guo, Shi-Min Hu Tsinghua University, Nankai University, Fitten Tech China
MaskFeat Masked feature prediction for self-supervised visual pre-training 380 Chen Wei, Christoph Feichtenhofer Facebook, Johns Hopkins University USA
GFP-GAN Towards real-world blind face restoration with generative facial prior 261 Xintao Wang, Ying Shan Tencent China
Multiresolution hash encoding Instant Neural Graphics Primitives with a Multiresolution Hash Encoding 1107 Thomas Muller, Alexander Keller NVIDIA Switzerland, UK, USA, Germany
Video VideoMAE VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training 362 Zhan Tong, Limin Wang Nanjing University, Tencent, Shanghai AI Lab China
Extension of MAE Masked Autoencoders As Spatiotemporal Learners 212 Christoph Feichtenhofer, Haoqi Fan, Kaiming He Meta USA
Make-A-Video Make-A-Video: Text-to-Video Generation without Text-Video Data 306 Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Devi Parikh, Sonal Gupta, Yaniv Taigman Meta USA
Speech Whisper Robust Speech Recognition via Large-Scale Weak Supervision 730 Alec Radford, Jong Wook Kim, Ilya Sutskever OpenAI USA
Multimodal Textual Inversions An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion 374 Rinon Gal, Daniel Cohen-Or Tel Aviv University, NVIDIA Israel, USA
Make-A-Scene Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors 217 Oran Gafni, Yaniv Taigman Meta USA
Magic3d Magic3d: High-resolution text-to-3d content creation 214 Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Tsung-Yi Lin NVIDIA USA
Blip-2 Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models 561 Junnan Li, Steven Hoi Salesforce Research USA
BLIP BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation 987 Junnan Li, Steven Hoi Salesforce Research USA
Parti Scaling autoregressive models for content-rich text-to-image generation 397 Jiahui Yu, Yonghui Wu Google USA
OFA OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework 522 Peng Wang, Chang Zhou Alibaba China
Gato A Generalist Agent 438 Scott Reed, Konrad Zolna,Emilio Parisotto, Nando de Freitas DeepMind USA
Data2vec Data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language 477 Alexei Baevski, Michael Auli Meta, SambaNova USA
LAION-5B LAION-5B: An Open Large-Scale Dataset for Training Next Generation Image-Text Models 642 Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev LAION, UC Berkeley, Gentec Data, TU Darmstadt, Hessian.AI, University of Washington Seattle, Technical University of Munich, Stability AI, Eleuther AI, Juelich Supercomputing Center (JSC) Research Center Juelich (FZJ) USA, Germany
LLM LLaMa Llama: Open and efficient foundation language models 1891 Hugo Touvron, Thibaut Lavril, Gautier Izacard, Edouard Grave, Guillaume Lample Meta USA
Self-consistency Self-consistency improves chain of thought reasoning in language models 325 Xuezhi Wang, Denny Zhou Google USA
PaLM-E Palm-e: An embodied multimodal language model 304 Danny Driess, Pete Florence Google, TU Berlin Germany
Palm 2 Palm 2 technical report 233 Google USA
PaLM PaLM: Scaling Language Modeling with Pathways 1869 Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel Google USA
OPT OPT: Open Pre-trained Transformer Language Models 875 Susan Zhang, Stephen Roller, Naman Goyal Meta USA
MT-NLG Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model 340 Shaden Smith, Mostofa Patwary, Bryan Catanzaro Microsoft, NVIDIA USA
LLaMa 2 Llama 2: Open foundation and fine-tuned chat models 554 Hugo Touvron, Thomas Scialom Meta USA
Zero-shot-CoT Large Language Models are Zero-Shot Reasoners 806 Takeshi Kojima, Yusuke Iwasawa The University of Tokyo Japan
Scratchpad Show your work: Scratchpads for intermediate computation with language models 248 Maxwell Nye, Augustus Odena MIT, Google USA
Minerva Solving Quantitative Reasoning Problems with Language Models 223 Aitor Lewkowycz, Behnam Neyshabur, Guy Gur-Ari, Vedant Misra Google USA
Least-to-most prompting Least-to-Most Prompting Enables Complex Reasoning in Large Language Models 313 Denny Zhou, Ed Chi Google USA
LaMDA LaMDA: Language Models for Dialog Applications 676 Romal Thoppilan, Quoc Le Google USA
InstructGPT Training language models to follow instructions with human feedback 2840 Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Paul Christiano, Jan Leike, Ryan Lowe OpenAI USA
HuggingChat Hugging Face USA
GPT-NeoX-20B GPT-NeoX-20B: An Open-Source Autoregressive Language Model 292 Sid Black, Stella Biderman, Eric Hallahan Eleuther AI USA
GPT-4 OpenAI USA
Flan finetuning Scaling instruction-finetuned language models 671 Hyung Won Chung, Le Hou, Shayne Longpre, Jason Wei Google USA
FLAN Finetuned language models are zero-shot learners 1065 Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Andrew M. Dai, Quoc Le Google USA
Flamingo Flamingo: a visual language model for few-shot learning 942 Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Karen Simonyan DeepMind USA
ERNIE Bot Baidu China
Emergent abilities Emergent Abilities of Large Language Models 805 Jason Wei, William Fedus Google, Stanford University，UNC Chapel Hill USA
Claude Anthropic USA
ChatGPT ChatGPT: Optimizing Language Models for Dialogue 551 OpenAI USA
Chain-of-Thought Prompting Chain of Thought Prompting Elicits Reasoning in Large Language Models 1542 Jason Wei, Denny Zhou Google USA
BLOOM BLOOM: A 176B-Parameter Open-Access Multilingual Language Model 609
Bard Google USA
Pali Pali: A jointly-scaled multilingual language-image model 210 Xi Chen, Radu Soricut Google USA
LLaVA Visual instruction tuning 279 Haotian Liu, Chunyuan Li, Yong Jae Lee University of Wisconsin-Madison, Microsoft, Columbia University USA
Inner monologue Inner monologue: Embodied reasoning through planning with language models 252 Wenlong Huang, Fei Xia, Ted Xiao Google USA
Constitutional AI Constitutional AI: Harmlessness from AI Feedback 234 Yuntao Bai, Jared Kaplan Anthropic USA
CoCoOP Conditional Prompt Learning for Vision-Language Models 421 Kaiyang Zhou, Ziwei Liu Nanyang Technological Universit Singapor
Evaluation Analysis PolyCoder A Systematic Evaluation of Large Language Models of Code 206 Frank F. Xu, Vincent J. Hellendoorn CMU USA
BIG-bench Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models 398
Design space of diffusion models Elucidating the design space of diffusion-based generative models 350 Tero Karras, Samuli Laine NVIDIA USA
Role of demonstrations Rethinking the role of demonstrations: What makes in-context learning work? 427 Sewon Min, Luke Zettlemoyer University of Washington, Meta, Allen Institute for AI USA
Fine-Tuning Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution 275 Ananya Kumar, Percy Liang Stanford University USA
Language Models as Zero-Shot Planners Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents 324 Wenlong Huang, Deepak Pathak, Igor Mordatch UC Berkeley, CMU, Google USA
Experiments with gpt-4 Sparks of artificial general intelligence: Early experiments with gpt-4 849 Sebastien Bubeck, Yi Zhang Microsoft USA
Deep Learning for Tabular Data Tabular Data: Deep Learning is Not All You Need 593 Ravid Shwartz-Ziv, Amitai Armon Intel USA
Analysis with gpt-3 What Makes Good In-Context Examples for GPT-3? 464 Jiachang Liu, Weizhu Chen Duke University, Microsoft USA
Gpts are gpts Gpts are gpts: An early look at the labor market impact potential of large language models 216 Tyna Eloundou, Sam Manning, Pamela Mishkin, Daniel Rock OpenAI, OpenResearch, University of Pennsylvania USA
Vision transformers are robust learners Vision transformers are robust learners 209 Sayak Paul, Pin-Yu Chen Carted, IBM USA
Evaluation of chatgpt A multitask, multilingual, multimodal evaluation of chatgpt on reasoning, hallucination, and interactivity 381 Yejin Bang, Pascale Fung The Hong Kong University of Science and Technology China
Tree-based models v.s. deep learning Why do tree-based models still outperform deep learning on tabular data? 354 Leo Grinsztajn, Gael Varoquaux Inria Saclay, Sorbonne University France
Quantifying Memorization Quantifying Memorization Across Neural Language Models 212 Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, Chiyuan Zhang Google, University of Pennsylvania, Cornell University USA
Diffusion Model Application Latent Diffusion Models High-Resolution Image Synthesis with Latent Diffusion Models 3361 Robin Rombach, Andreas Blattmann, Bjorn Ommer Ludwig Maximilian University of Munich IWR, Heidelberg University, Runway Germany
Imagic Imagic: Text-Based Real Image Editing with Diffusion Models 259 Bahjat Kawar, Shiran Zada, Michal Irani Google, Technion, Weizmann Institute of Science USA, Israel
Imagen video Imagen video: High definition video generation with diffusion models 330 Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Tim Salimans Google USA
Imagen Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding 1754 Chitwan Saharia, William Chan, Mohammad Norouzi Google Canada
Hierarchical Text-Conditional Image Generation Hierarchical Text-Conditional Image Generation with CLIP Latents 2521 Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen OpenAI USA
GeoDiff GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation 216 Minkai Xu, Stefano Ermon, Jian Tang Mila-Quebec AI Institute, University of Montreal, Stanford University, HEC Montreal, CIFAR Canada, USA
Gen2 Runway Germany
eDiffi eDiffi: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers 213 Yogesh Balaji, Ming-Yu Liu NVIDIA USA
DreamFusion DreamFusion: Text-to-3D using 2D Diffusion 419 Ben Poole, Ben Mildenhall Google, UC Berkeley USA
DreamBooth DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation 495 Nataniel Ruiz, Kfir Aberman Google, Boston University USA
Dpm-solver Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps 286 Cheng Lu, Jianfei Chen, Jun Zhu BNRist, Tsinghua University, Renmin University of China China
Diffusion-LM Diffusion-LM Improves Controllable Text Generation 241 Xiang Lisa Li, Tatsunori B. Hashimoto Stanford University USA
DDRM Denoising Diffusion Restoration Models 226 Bahjat Kawar, Jiaming Song Technion, Stanford University, NVIDIA Israel, USA
ControlNet Adding conditional control to text-to-image diffusion models 410 Lvmin Zhang, Maneesh Agrawala Stanford University USA
Classifier-free guidance Classifier-Free Diffusion Guidance 865 Jonathan Ho, Tim Salimans Google USA
Card Card: Classification and regression diffusion models 448 Xizewen Han, Huangjie Zheng, Mingyuan Zhou The University of Texas at Austin USA
Detection Segmentation YOLOv7 YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors 2226 Chien-Yao Wang, Hong-Yuan Mark Liao Institute of Information Science Academia Sinica China
YOLOv6 YOLOv6: A single-stage object detection framework for industrial applications 553 Chuyi Li, Lulu Li, Hongliang Jiang, Kaiheng Weng, Yifei Geng, Liang Li, Zaidan Ke, Qingyuan Li, Meng Cheng, Weiqiang Nie, Yiduo Li, Bo Zhang, Xiaoming Xu Meituan China
ViTDet Exploring Plain Vision Transformer Backbones for Object Detection 327 Yanghao Li, Ross Girshick, Kaiming He Facebook USA
Swin UNETR Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images 319 Ali Hatamizadeh, Daguang Xu NVIDIA, Vanderbilt University USA
Segment anything Segment anything 963 Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Piotr Dollar, Ross Girshick Meta USA
PETR PETR: Position Embedding Transformation for Multi-View 3D Object Detection 201 Yingfei Liu, Tiancai Wang, Jian Sun MEGVII China
Dino Dino: Detr with improved denoising anchor boxes for end-to-end object detection 397 Hao Zhang, Feng Li, Shilong Liu, Lei Zhang The Hong Kong University of Science and Technology, Tsinghua University, International Digital Economy Academy China
Bytetrack Bytetrack: Multi-object tracking by associating every detection box 587 Yifu Zhang, Xinggang Wang Huazhong University of Science and Technology, The University of Hong Kong, ByteDance China
DN-DETR DN-DETR: Accelerate DETR Training by Introducing Query DeNoising 245 Feng Li, Hao Zhang, Lei Zhang The Hong Kong University of Science and Technology, Tsinghua University, IDEA China
Detic Detecting Twenty-thousand Classes using Image-level Supervision 239 Xingyi Zhou, Ishan Misra Meta, The University of Texas at Austin USA
AI4Science SignalP 6.0 SignalP 6.0 predicts all five types of signal peptides using protein language models 650 Felix Teufel, Henrik Nielsen Technical University of Denmark, ETH Zurich, University of Copenhagen, Stanford University, Copenhagen University Hospital, Wellcome Genome Campus, Stockholm University Denmark, Switzerland, USA, UK, Sweden
Galactica Galactica: A Large Language Model for Science 220 Ross Taylor, Robert Stojnic Meta USA
RL-designed magnetic controller Magnetic control of tokamak plasmas through deep reinforcement learning 417 Jonas Degrave, Federico Felici, Jonas Buchli, Michael Neunert, Brendan Tracey DeepMind, EPFL UK, Switzerland
ESMFold Evolutionary-scale prediction of atomic-level protein structure with a language model 451 Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Alexander Rives Meta,New York University, Stanford University, MIT USA
EDM Equivariant Diffusion for Molecule Generation in 3D 235 Emiel Hoogeboom, Victor Garcia Satorras, Clement Vignac, Max Welling University of Amsterdam, EPFL Netherlands, Switzerland
ColabFold ColabFold: making protein folding accessible to all 2624 Milot Mirdita, Sergey Ovchinnikov, Martin Steinegger Max Planck Institute for Multidisciplinary Sciences, Seoul National University, The University of Tokyo, Michigan State University, Harvard University Germany,South Korea, Japan, USA
AlphaFold DB AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models 2989 Mihaly Varadi, Demis Hassabis, Sameer Velankar DeepMind UK
AI4Others AlphaTensor Discovering faster matrix multiplication algorithms with reinforcement learning 267 Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Pushmeet Kohli DeepMind USA
AlphaCode Competition-Level Code Generation with AlphaCode 382 Yujia Li, David Choi, Junyoung Chung, Nate Kushman , Julian Schrittwieser, Remi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Oriol Vinyals DeepMind USA
Robots Learning robust perceptive locomotion Learning robust perceptive locomotion for quadrupedal robots in the wild 331 Takahiro Miki ETH Zurich, KAIST, Intel Switzerland, Korea, USA
SayCan Do As I Can, Not As I Say: Grounding Language in Robotic Affordances 510 Google USA
Ensemble Model soups Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time 333 Mitchell Wortsman, Yair Carmon, Simon Kornblith, Ludwig Schmidt University of Washington, Columbia University, Google, Meta, Tel Aviv University USA, Israel
AI4Others Symbiotic Creativity Pathway to Future Symbiotic Creativity 1 Yike Guo HKUST China
Detection Segmentation OSTrack Joint feature learning and relation modeling for tracking: A one-stream framework 118 Botao Ye, Xilin Chen ICT CAS China


人工智能杰出人才

贡献者 机构 国家
Denny Zhou Google USA
Jason Wei Google USA
Daniel Cohen-Or Tel Aviv University Israel
Junnan Li Salesforce Research USA
Steven Hoi Salesforce Research USA
Takahiro Miki ETH Zurich Switzerland
Yike Guo HKUST China
Bahjat Kawar Google USA
Christoph Feichtenhofer Meta USA
Han Hu Microsoft Research Asia China
Hugo Touvron Meta USA
Jonathan Ho Google USA
Tim Salimans Google USA
Kaiming He Meta USA
Quoc Le Google USA
Wenlong Huang Google USA
Yaniv Taigman Meta USA
Feng Li The Hong Kong University of Science and Technology China
Hao Zhang The Hong Kong University of Science and Technology China
Lei Zhang International Digital Economy Academy China
Chitwan Saharia Google USA
William Chan Google USA
Alexander Keller NVIDIA Germany
Alexei Baevski Meta USA
Ali Hatamizadeh NVIDIA USA
Amir Hertz Tel Aviv University Israel
Amitai Armon Intel USA
Ananya Kumar Stanford University USA
Asher Trockman CMU USA
Augustus Odena Google USA
Ben Mildenhall Google USA
Ben Poole Google USA
Botao Ye ICT CAS China
Chang Zhou Alibaba China
Chen Wei Facebook USA
Chien-Yao Wang Institute of Information Science Academia Sinica China
Daguang Xu USA USA
Danny Driess Google Germany
Ed Chi Google USA
Felix Teufel Technical University of Denmark Denmark
Frank F. Xu CMU USA
Gael Varoquaux Inria Saclay France
Henrik Kretzschmar Waymo USA
Henrik Nielsen Technical University of Denmark Denmark
Hong-Yuan Mark Liao Institute of Information Science Academia Sinica China
Ishan Misra Meta USA
J. Zico Kolter CMU USA
Jared Kaplan Anthropic USA
Jiachang Liu Duke University USA
Jiahui Yu Google USA
Jiaming Song NVIDIA USA
Kaiyang Zhou Nanyang Technological Universit Singapor
Kfir Aberman Google USA
Leo Grinsztajn Inria Saclay France
Limin Wang Nanjing University China
Luc Van Gool KU Leuven Belgium
Luke Zettlemoyer University of Washington USA
Luming Tang Cornell University USA
Lvmin Zhang Stanford University USA
Maneesh Agrawala Stanford University USA
Matthew Tancik UC Berkeley USA
Maxwell Nye Google USA
Meng-Hao Guo Tsinghua University China
Michael Auli Meta USA
Ming-Yu Liu NVIDIA USA
Namuk Park Yonsei University Korea
Nataniel Ruiz Google USA
Oran Gafni Meta USA
Pascale Fung The Hong Kong University of Science and Technology China
Peng Wang Alibaba China
Percy Liang Stanford University USA
Pete Florence Google Germany
Pin-Yu Chen IBM USA
Radu Soricut Google USA
Ravid Shwartz-Ziv Intel USA
Rinon Gal Tel Aviv University Israel
Robert Stojnic Meta USA
Romal Thoppilan Google USA
Roman Suvorov Samsung AI Center Moscow Russia
Ross Girshick Facebook USA
Ross Taylor Meta USA
Saining Xie Facebook USA
Samuli Laine NVIDIA USA
Sayak Paul Carted USA
Sebastien Bubeck Microsoft USA
Sewon Min University of Washington USA
Shi-Min Hu Tsinghua University China
Songkuk Kim Yonsei University Korea
Takeshi Kojima The University of Tokyo Japan
Tatsunori B. Hashimoto Stanford University USA
Tero Karras NVIDIA USA
Thomas Muller NVIDIA Switzerland
Thomas Scialom Meta USA
Victor Lempitsky Samsung AI Center Moscow Russia
Vincent J. Hellendoorn CMU USA
Weizhu Chen Microsoft USA
William Fedus Google USA
Xi Chen Google USA
Xiang Lisa Li Stanford University USA
Xiangyu Zhang MEGVII China
Xiaohan Ding BNRist China
Xilin Chen ICT CAS China
Xinggang Wang Huazhong University of Science and Technology China
Xingyi Zhou Meta USA
Xintao Wang Tencent China
Xuezhi Wang Google USA
Yawei Li ETH Zurich Switzerland
Yejin Bang The Hong Kong University of Science and Technology China
Yi Zhang Microsoft USA
Yifu Zhang Huazhong University of Science and Technology China
Ying Shan Tencent China
Yogesh Balaji NVIDIA USA
Yonghui Wu Google USA
Yuntao Bai Anthropic USA
Yusuke Iwasawa The University of Tokyo Japan
Ze Liu Microsoft Research Asia China
Zhan Tong Nanjing University China
Zhuang Liu Facebook USA
Ziwei Liu Nanyang Technological Universit Singapor
Ludwig Schmidt University of Washington Seattle USA
Pamela Mishkin OpenAI USA
Alec Radford OpenAI USA
Aleksander Holynski UC Berkeley USA
Alexander Kolesnikov Google Switzerland
Alexei A. Efros UC Berkeley USA
Andreas Blattmann Heidelberg University Germany
Anpei Chen ShanghaiTech University China
Bjorn Ommer Heidelberg University Germany
Bryan Catanzaro NVIDIA USA
Chang Xu University of Sydney Australia
Cheng Lu Tsinghua University China
Chunyuan Li Microsoft USA
Deepak Pathak CMU USA
Demis Hassabis DeepMind UK
Eric Hallahan Eleuther AI USA
Fei Xia Google USA
Hao Su UC San Diego USA
Haoqi Fan Meta USA
Haotian Liu University of Wisconsin-Madison USA
Huangjie Zheng The University of Texas at Austin USA
Igor Mordatch Google USA
Ilya Sutskever OpenAI USA
Jian Sun MEGVII China
Jian Tang Mila-Quebec AI Institute Canada
Jianfei Chen Tsinghua University China
Jianyuan Guo University of Sydney Australia
Jong Wook Kim OpenAI USA
Jun Zhu Tsinghua University China
Lucas Beyer Google Switzerland
Martin Steinegger Seoul National University Korea
Menglin Jia Cornell University USA
Michal Irani Google USA
Mihaly Varadi DeepMind UK
Milot Mirdita Max Planck Institute for Multidisciplinary Sciences Germany
Mingyuan Zhou The University of Texas at Austin USA
Minkai Xu Mila-Quebec AI Institute Canada
Mohammad Norouzi Google USA
Mostofa Patwary NVIDIA USA
Naman Goyal Meta USA
Robin Rombach Heidelberg University Germany
Sameer Velankar DeepMind UK
Ser-Nam Lim University of Copenhagen USA
Sergey Ovchinnikov Harvard University USA
Shaden Smith Microsoft USA
Shiran Zada Google USA
Sid Black Eleuther AI USA
Stefano Ermon Stanford University USA
Stella Biderman Eleuther AI USA
Stephen Roller Meta USA
Susan Zhang Meta USA
Ted Xiao Google USA
Tiancai Wang MEGVII China
Tim Brooks UC Berkeley USA
Xiaohua Zhai Google Switzerland
Xizewen Han The University of Texas at Austin USA
Yanghao Li Facebook USA
Yingfei Liu MEGVII China
Yong Jae Lee University of Wisconsin-Madison USA
Yunhe Wang Huawei Noahs Ark Lab China
Zexiang Xu Adobe China
Aitor Lewkowycz Google USA
Behnam Neyshabur Google USA
Clement Vignac EPFL Switzerland
Daniel Rock University of Pennsylvania USA
Emiel Hoogeboom University of Amsterdam Netherlands
Emilio Parisotto DeepMind USA
Guy Gur-Ari Google USA
Hongyang Li Shanghai AI Laboratory China
Hyung Won Chung Google USA
Jifeng Dai Shanghai AI Laboratory China
Konrad Zolna DeepMind USA
Le Hou Google USA
Max Welling University of Amsterdam Netherlands
Mitchell Wortsman University of Washington USA
Nando de Freitas DeepMind USA
Sam Manning OpenAI USA
Scott Reed DeepMind USA
Shayne Longpre Google USA
Shilong Liu Tsinghua University China
Simon Kornblith Google USA
Tyna Eloundou OpenAI USA
Vedant Misra Google USA
Victor Garcia Satorras University of Amsterdam Netherlands
Wenhai Wang Shanghai AI Laboratory China
Yair Carmon Tel Aviv University Israel
Yue Cao Microsoft Research Asia China
Zhenda Xie Tsinghua University China
Zheng Zhang Microsoft Research Asia China
Zhiqi Li Shanghai AI Laboratory China
Thomas Hubert DeepMind USA
Aditya Ramesh OpenAI USA
Alex Nichol OpenAI USA
Alexander Rives Meta USA
Antoine Miech DeepMind USA
Brendan Tracey DeepMind UK
Brian Hie Meta USA
Casey Chu OpenAI USA
Edouard Grave Meta USA
Federico Felici EPFL Switzerland
Gautier Izacard Meta USA
Guillaume Lample Meta USA
Halil Akin Meta USA
Jay Whang Google USA
Jean-Baptiste Alayrac DeepMind USA
Jeff Donahue DeepMind USA
Jonas Buchli DeepMind UK
Jonas Degrave DeepMind UK
Karen Simonyan DeepMind USA
Mark Chen OpenAI USA
Michael Neunert DeepMind UK
Pauline Luc DeepMind USA
Prafulla Dhariwal OpenAI USA
Roshan Rao Meta USA
Thibaut Lavril Meta USA
Zeming Lin Meta USA
Aja Huang DeepMind USA
Alexander Kirillov Meta USA
Alhussein Fawzi DeepMind USA
Andrew M. Dai Google USA
Bernardino Romera-Paredes DeepMind USA
Chen-Hsuan Lin NVIDIA USA
Chiyuan Zhang Google USA
Daphne Ippolito Google USA
Eric Mintun Meta USA
Florian Tramer Google USA
Hanzi Mao Meta USA
Jun Gao NVIDIA USA
Katherine Lee Google USA
Kelvin Guu Google USA
Maarten Bosma Google USA
Matej Balog DeepMind USA
Matthew Jagielski Google USA
Nicholas Carlini Google USA
Nikhila Ravi Meta USA
Piotr Dollar Meta USA
Pushmeet Kohli DeepMind USA
Towaki Takikawa NVIDIA USA
Tsung-Yi Lin NVIDIA USA
Vincent Y. Zhao Google USA
Xiaohui Zeng NVIDIA USA
Adam Polyak Meta USA
Devi Parikh Meta USA
Sonal Gupta Meta USA
Thomas Hayes Meta USA
Uriel Singer Meta USA
Xi Yin Meta USA
Aakanksha Chowdhery Google USA
Douglas Eck Google USA
Jacob Devlin Google USA
Jeff Dean Google USA
Kathy Meier-Hellstern Google USA
Noah Fiedel Google USA
Sharan Narang Google USA
Slav Petrov Google USA
Cade Gordon UC Berkeley USA
Carroll L. Wainwright OpenAI USA
Christoph Schuhmann LAION USA
Diogo Almeida OpenAI USA
Jan Leike OpenAI USA
Jeff Wu OpenAI USA
Jenia Jitsev LAION USA
Long Ouyang OpenAI USA
Mehdi Cherti LAION USA
Paul Christiano OpenAI USA
Richard Vencu LAION USA
Robert Kaczmarczyk LAION USA
Romain Beaumont LAION USA
Ross Wightman LAION USA
Ryan Lowe OpenAI USA
Xu Jiang OpenAI USA
Bo Zhang Meituan China
Chuyi Li Meituan China
Hongliang Jiang Meituan China
Kaiheng Weng Meituan China
Liang Li Meituan China
Lulu Li Meituan China
Meng Cheng Meituan China
Qingyuan Li Meituan China
Weiqiang Nie Meituan China
Xiaoming Xu Meituan China
Yiduo Li Meituan China
Yifei Geng Meituan China
Zaidan Ke Meituan China
Agustin Dal Lago DeepMind USA
Cyprien de Masson d'Autume DeepMind USA
David Choi DeepMind USA
Felix Gimeno DeepMind USA
James Keeling DeepMind USA
Julian Schrittwieser DeepMind USA
Junyoung Chung DeepMind USA
Nate Kushman DeepMind USA
Oriol Vinyals DeepMind USA
Peter Choy DeepMind USA
Remi Leblond DeepMind USA
Tom Eccles DeepMind USA
Yujia Li DeepMind USA


人工智能杰出机构

排名 机构 分数 国家
1 Google 27.87 USA
2 Meta 12.12 USA
3 NVIDIA 5.83 USA
4 OpenAI 5.33 USA
5 Stanford University 4.26 USA
6 UC Berkeley 2.77 USA
7 Microsoft 2.33 USA
8 Anthropic 2.00 USA
8 Salesforce Research 2.00 USA
9 Tsinghua University 1.92 China
10 CMU 1.83 USA
11 The Hong Kong University of Science and Technology 1.67 China
12 The University of Texas at Austin 1.50 USA
13 EPFL 1.33 Switzerland
13 Intel 1.33 USA
13 Microsoft Research Asia 1.33 China
13 Runway 1.33 Germany
13 Tencent 1.33 China
14 MEGVII 1.25 China
15 Tel Aviv University 1.20 Israel
15 The University of Tokyo 1.20 Japan
16 Eleuther AI 1.10 USA
17 Alibaba 1.00 China
17 Baidu 1.00 China
17 HKUST 1.00 China
17 Hugging Face 1.00 USA
17 ICT CAS 1.00 China
17 Institute of Information Science Academia Sinica 1.00 China
17 Meituan 1.00 China
17 Nanyang Technological Universit 1.00 Singapor
18 ETH Zurich 0.98 Switzerland
19 MIT 0.75 USA
20 Cornell University 0.67 USA
20 Nanjing University 0.67 China
20 Shanghai AI Lab 0.67 China
20 Technion 0.67 USA
20 The University of Hong Kong 0.67 China
20 University of Pennsylvania 0.67 USA
21 BNRist 0.58 China
22 Columbia University 0.53 USA
22 University of Washington 0.53 USA
23 Bosch Center for AI 0.50 USA
23 Boston University 0.50 USA
23 Carted 0.50 USA
23 Duke University 0.50 USA
23 Huawei 0.50 China
23 IBM 0.50 USA
23 Inria Saclay 0.50 France
23 Johns Hopkins University 0.50 USA
23 KU Leuven 0.50 Belgium
23 NAVER AI Lab 0.50 Korea
23 SambaNova 0.50 USA
23 Sorbonne University 0.50 France
23 TU Berlin 0.50 Germany
23 University of Amsterdam 0.50 Netherlands
23 University of Sydney 0.50 Australia
23 Vanderbilt University 0.50 USA
23 Yonsei University 0.50 Korea
24 University of Copenhagen 0.48 USA
25 Allen Institute for AI 0.33 USA
25 ByteDance 0.33 China
25 Fitten Tech 0.33 China
25 Heidelberg University 0.33 Germany
25 Huazhong University of Science and Technology 0.33 China
25 International Digital Economy Academy 0.33 China
25 KAIST 0.33 Korea
25 Ludwig Maximilian University of Munich & IWR 0.33 Germany
25 Nankai University 0.33 China
25 OpenResearch 0.33 USA
25 Renmin University of China 0.33 China
25 Samsung 0.33 Korea
25 Skolkovo Institute of Science and Technology 0.33 Russia
25 UNC Chapel Hill 0.33 USA
25 University of Wisconsin-Madison 0.33 USA
25 Waymo 0.33 USA
25 Weizmann Institute of Science 0.33 Israel
25 Xian Jiaotong University 0.33 China
26 Aberystwyth University 0.25 USA
26 Adobe 0.25 China
26 New York University 0.25 USA
26 ShanghaiTech University 0.25 China
26 UC San Diego 0.25 USA
26 University of Tubingen 0.25 Germany
27 CIFAR 0.20 Canada
27 HEC Montreal 0.20 Canada
27 Harvard University 0.20 USA
27 Max Planck Institute for Multidisciplinary Sciences 0.20 Germany
27 Michigan State University 0.20 USA
27 Mila-Quebec AI Institute 0.20 Canada
27 Seoul National University 0.20 Korea
27 University of Montreal 0.20 Canada
28 Copenhagen University Hospital 0.14 Denmark
28 Stockholm University 0.14 Sweden
28 Technical University of Denmark 0.14 Denmark
28 Wellcome Genome Campus 0.14 USA
29 Gentec Data 0.10 USA
29 Hessian.AI 0.10 USA
29 Juelich Supercomputing Center (JSC) Research Center Juelich   (FZJ) 0.10 USA
29 LAION 0.10 USA
29 Stability AI 0.10 USA
29 TU Darmstadt 0.10 Germany
29 Technical University of Munich 0.10 Germany
29 University of Washington Seattle 0.10 USA


人工智能杰出国家

排名 国家 分数
1 USA 76.87
2 China 19.33
3 Germany 3.83
4 Switzerland 3.62
5 Israel 2.50
6 UK 2.45
7 Korea 1.67
8 Canada 1.50
9 Japan 1.25
10 France 1.00
10 Singapor 1.00
11 Denmark 0.70
12 Australia 0.50
12 Belgium 0.50
12 Netherlands 0.50
13 Russia 0.33
14 South Korea 0.25
15 Sweden 0.20