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Quanquan Gu

2008–2026 年に発表

別表記
Quanquan, Gu
364
論文数
18,898
被引用数
75
h 指数
255
i10 指数

被引用数

Quanquan Gu の年別被引用数1967 年: 被引用 1 件1988 年: 被引用 1 件1989 年: 被引用 1 件1999 年: 被引用 1 件2001 年: 被引用 2 件2007 年: 被引用 1 件2008 年: 被引用 6 件2009 年: 被引用 6 件2010 年: 被引用 21 件2011 年: 被引用 40 件2012 年: 被引用 65 件2013 年: 被引用 94 件2014 年: 被引用 178 件2015 年: 被引用 206 件2016 年: 被引用 266 件2017 年: 被引用 359 件2018 年: 被引用 431 件2019 年: 被引用 637 件2020 年: 被引用 922 件2021 年: 被引用 1,244 件2022 年: 被引用 997 件2023 年: 被引用 890 件2024 年: 被引用 1,320 件2025 年: 被引用 1,672 件2026 年: 被引用 547 件2027 年: 被引用 1 件1968〜1987 年は被引用が無いため表示していません1990〜1998 年は被引用が無いため表示していません2000 年は被引用が無いため表示していません2002〜2006 年は被引用が無いため表示していません

引用元

国・地域

この著者を引用した国・地域の世界地図中国: 引用元論文 2,428 件、この内訳の 28.8%アメリカ合衆国: 引用元論文 2,192 件、この内訳の 26%イギリス: 引用元論文 380 件、この内訳の 4.5%オーストラリア: 引用元論文 304 件、この内訳の 3.6%香港: 引用元論文 264 件、この内訳の 3.1%カナダ: 引用元論文 245 件、この内訳の 2.9%ドイツ: 引用元論文 216 件、この内訳の 2.6%フランス: 引用元論文 201 件、この内訳の 2.4%シンガポール: 引用元論文 199 件、この内訳の 2.4%インド: 引用元論文 186 件、この内訳の 2.2%日本: 引用元論文 167 件、この内訳の 2%イタリア: 引用元論文 134 件、この内訳の 1.6%
0%28.8%その他 17.9%

機関

分野

  • Computer Science66.3%
  • Engineering6.7%
  • Medicine5.3%
  • Decision Sciences4.7%
  • Mathematics3.6%
  • Physics and Astronomy3.5%
  • その他9.9%

トピック

  • Topic Modeling4.7%
  • Advanced Graph Neural Networks4.1%
  • Recommender Systems and Techniques3.7%
  • Stochastic Gradient Optimization Techniques3.6%
  • Adversarial Robustness in Machine Learning3.4%
  • Face and Expression Recognition2.4%
  • その他78.1%

共著者

全論文

検索で開く
  1. TrustLLM: Trustworthiness in Large Language Models

    著者: Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao - arXiv (Cornell University), CoRR 2024 被引用: 410

  2. Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

    著者: Zixiang Chen, Yihe Deng, Huizhuo Yuan, Kaixuan Ji, Quanquan Gu - ICML 2024 被引用: 607

  3. Self-Play Preference Optimization for Language Model Alignment

    著者: Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu - ICLR 2025 被引用: 266

  4. Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

    著者: Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Dhagash Mehta, Stefano Pasquali, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Jian Pei, Carl Yang, Liang Zhao - ACM Computing Surveys, ACM Comput. Surv. 2025 被引用: 157

  5. Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves

    著者: Yihe Deng, Weitong Zhang, Zixiang Chen, Quanquan Gu - arXiv (Cornell University), CoRR 2023 被引用: 102

  6. Personalized entity recommendation: a heterogeneous information network approach

    著者: Xiao Yu, Xiang Ren, Yizhou Sun, Quanquan Gu, Bradley Sturt, Urvashi Khandelwal, Brandon Norick, Jiawei Han - international conference on Web search and data mining, WSDM 2014 被引用: 745

  7. LLaVA-Critic: Learning to Evaluate Multimodal Models

    著者: Tianyi Xiong, Xiyao Wang, Dong Guo, Qinghao Ye, Haoqi Fan, Quanquan Gu, Heng Huang, Chunyuan Li - IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025 被引用: 87

  8. Towards Understanding the Spectral Bias of Deep Learning

    著者: Yuan Cao, Zhiying Fang, Yue Wu, Ding-Xuan Zhou, Quanquan Gu - Thirtieth International Joint Conference on Artificial Intelligence, IJCAI 2021 被引用: 153

  9. Diffusion Language Models Are Versatile Protein Learners

    著者: Xinyou Wang, Zaixiang Zheng, Fei Ye, Dongyu Xue, Shujian Huang, Quanquan Gu - ICML 2024 被引用: 136

  10. How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?

    著者: Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Peter L. Bartlett - ICLR 2024 被引用: 102

  11. Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

    著者: Estee Y. Cramer, Evan L Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Katie House, Yuxin Huang, Dasuni Jayawardena, Abdul Hannan Kanji, Ayush Khandelwal, Khoa Le, Anja Mühlemann, Jarad Niemi, Apurv Shah, Ariane Stark, Yijin Wang, Nutcha Wattanachit, Martha Zorn, Youyang Gu, Sansiddh Jain, Nayana Bannur, Ayush Deva, Mihir Kulkarni, Srujana Merugu, Alpan Raval, Siddhant Shingi, Avtansh Tiwari, Jerome White, Neil F. Abernethy, Spencer Woody, Maytal Dahan, Spencer J. Fox, Kelly Gaither, Michael Lachmann, Lauren Ancel Meyers, James G. Scott, Mauricio Tec, Ajitesh Srivastava, Glover George, Jeffrey C. Cegan, Ian Dettwiller, William P. England, Matthew W. Farthing, Robert H. Hunter, Brandon J. Lafferty, Igor Linkov, Michael L. Mayo, Matthew Parno, Michael A. Rowland, Benjamin D. Trump, Yanli Zhang‐James, Samuel Chen, Stephen V. Faraone, Jonathan Hess, Christopher P. Morley, Asif Salekin, Dongliang Wang, Sabrina Corsetti, T. M. Baer, Marisa C. Eisenberg, Karl Falb, Yitao Huang, Emily T. Martin, Ella McCauley, Robert L. Myers, Tom Schwarz, Daniel Sheldon, Graham Gibson, Rose Yu, Liyao Gao, Yi-An Ma, Dongxia Wu, Xifeng Yan, Xiaoyong Jin, Yu-Xiang Wang, YangQuan Chen, Lihong Guo, Yanting Zhao, Quanquan Gu, Jinghui Chen, Lingxiao Wang, Pan Xu, Weitong Zhang, Difan Zou, Hannah Biegel, J. Lega, Steve McConnell, VP Nagraj, Stephanie Guertin, Christopher Hulme-Lowe, Stephen Turner, Yunfeng Shi, Xuegang Ban, Robert Walraven, Qi‐Jun Hong, Stanley Kong, Axel van de Walle ほか 195 名 - National Academy of Sciences, Proceedings of the National Academy of Sciences 2022 被引用: 320

  12. Mitigating Object Hallucination in Large Vision-Language Models via Classifier-Free Guidance

    著者: Linxi Zhao, Yihe Deng, Weitong Zhang, Quanquan Gu - ICML 2025 被引用: 50

  13. DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design

    著者: Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu - ICML 2023 被引用: 137

  14. Is neuron coverage a meaningful measure for testing deep neural networks?

    著者: Fabrice Harel-Canada, Lingxiao Wang, Muhammad Ali Gulzar, Quanquan Gu, Miryung Kim - Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/SIGSOFT FSE 2020 被引用: 151

  15. Towards Understanding Mixture of Experts in Deep Learning

    著者: Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li - arXiv (Cornell University), CoRR 2022 被引用: 66

  16. Generalized Fisher Score for Feature Selection

    著者: Quanquan Gu, Zhenhui Li, Jiawei Han - http://faculty.ist.psu.edu/jessieli/Publications/uai11.pdf 2011 被引用: 461

  17. DPLM-2: A Multimodal Diffusion Protein Language Model

    著者: Xinyou Wang, Zaixiang Zheng, Fei Ye, Dongyu Xue, Shujian Huang, Quanquan Gu - ICLR 2025 被引用: 75

  18. Enhancing Large Vision Language Models with Self-Training on Image Comprehension

    著者: Yihe Deng, Pan Lu, Fan Yin, Ziniu Hu, Sheng Shen, Quanquan Gu, James Y. Zou, Kai-Wei Chang, Wei Wang - Advances in Neural Information Processing Systems 37, NeurIPS 2024 被引用: 93

  19. Reinforcement Learning from Human Feedback with Active Queries

    著者: Kaixuan Ji, Jiafan He, Quanquan Gu - Trans. Mach. Learn. Res. 2025 被引用: 37

  20. Neural Thompson Sampling

    著者: Weitong Zhang, Dongruo Zhou, Lihong Li, Quanquan Gu - ICLR 2021 被引用: 159

  21. Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning

    著者: Jiasheng Ye, Zaixiang Zheng, Yu Bao, Lihua Qian, Quanquan Gu - arXiv (Cornell University), CoRR 2023 被引用: 36

  22. Improving Adversarial Robustness Requires Revisiting Misclassified Examples

    著者: Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu - International Conference on Learning Representations, ICLR 2020 被引用: 851

  23. Gradient descent optimizes over-parameterized deep ReLU networks

    著者: Difan Zou, Yuan Cao, Dongruo Zhou, Quanquan Gu - Machine Learning, Mach. Learn. 2019 被引用: 226

  24. Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation

    著者: Huizhuo Yuan, Zixiang Chen, Kaixuan Ji, Quanquan Gu - Advances in Neural Information Processing Systems 37, NeurIPS 2024 被引用: 94