Chengxu Zhuang

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 23

Top Topics

Supervised Learning

Visual Representations

Top Venues

Publications

Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling. ACL (Findings) (2024)
Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling. CoRR (2024)
Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
Visual Grounding Helps Learn Word Meanings in Low-Data Regimes. NAACL-HLT (2024)
Bria Long, Violet Xiang, Stefan Stojanov, Robert Z. Sparks, Zi Yin, Grace E. Keene, Alvin W. M. Tan, Steven Y. Feng, Chengxu Zhuang, Virginia A. Marchman, Daniel L. K. Yamins, Michael C. Frank
The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiences. CoRR (2024)
Leshem Choshen, Ryan Cotterell, Michael Y. Hu, Tal Linzen, Aaron Mueller, Candace Ross, Alex Warstadt, Ethan Wilcox, Adina Williams, Chengxu Zhuang
[Call for Papers] The 2nd BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus. CoRR (2024)
Aran Nayebi, Nathan C. L. Kong, Chengxu Zhuang, Justin L. Gardner, Anthony M. Norcia, Daniel L. K. Yamins
Mouse visual cortex as a limited resource system that self-learns an ecologically-general representation. PLoS Comput. Biol. 19 (10) (2023)
Alex Warstadt, Leshem Choshen, Aaron Mueller, Adina Williams, Ethan Wilcox, Chengxu Zhuang
Call for Papers - The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus. CoRR (2023)
Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
Visual Grounding Helps Learn Word Meanings in Low-Data Regimes. CoRR (2023)
Chengxu Zhuang, Ziyu Xiang, Yoon Bai, Xiaoxuan Jia, Nicholas B. Turk-Browne, Kenneth A. Norman, James J. DiCarlo, Dan Yamins
How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning? NeurIPS (2022)
Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
Conditional Negative Sampling for Contrastive Learning of Visual Representations. ICLR (2021)
Chengxu Zhuang, Siming Yan, Aran Nayebi, Martin Schrimpf, Michael C. Frank, James J. DiCarlo, Daniel L. K. Yamins
Unsupervised neural network models of the ventral visual stream. Proc. Natl. Acad. Sci. USA 118 (3) (2021)
Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
Conditional Negative Sampling for Contrastive Learning of Visual Representations. CoRR (2020)
Mike Wu, Chengxu Zhuang, Milan Mosse, Daniel Yamins, Noah D. Goodman
On Mutual Information in Contrastive Learning for Visual Representations. CoRR (2020)
Chengxu Zhuang, Tianwei She, Alex Andonian, Max Sobol Mark, Daniel Yamins
Unsupervised Learning From Video With Deep Neural Embeddings. CVPR (2020)
Chengxu Zhuang, Xuehao Ding, Divyanshu Murli, Daniel Yamins
Local Label Propagation for Large-Scale Semi-Supervised Learning. CoRR (2019)
Chengxu Zhuang, Alex Lin Zhai, Daniel Yamins
Local Aggregation for Unsupervised Learning of Visual Embeddings. ICCV (2019)
Chengxu Zhuang, Alex Lin Zhai, Daniel Yamins
Local Aggregation for Unsupervised Learning of Visual Embeddings. CoRR (2019)
Chengxu Zhuang, Alex Andonian, Daniel Yamins
Unsupervised Learning from Video with Deep Neural Embeddings. CoRR (2019)
Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Joshua B. Tenenbaum, Daniel L. K. Yamins
Flexible Neural Representation for Physics Prediction. CoRR (2018)
Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Josh Tenenbaum, Daniel L. Yamins
Flexible neural representation for physics prediction. NeurIPS (2018)
Chengxu Zhuang, Yulong Wang, Daniel Yamins, Xiaolin Hu
Deep Learning Predicts Correlation between a Functional Signature of Higher Visual Areas and Sparse Firing of Neurons. Frontiers Comput. Neurosci. 11 (2017)
Chengxu Zhuang, Jonas Kubilius, Mitra J. Z. Hartmann, Daniel Yamins
Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System. CoRR (2017)
Chengxu Zhuang, Jonas Kubilius, Mitra J. Z. Hartmann, Daniel L. Yamins
Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System. NIPS (2017)
Mingmin Zhao, Chengxu Zhuang, Yizhou Wang, Tai Sing Lee
Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction. ICLR (Workshop) (2015)