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2020 – today
- 2024
[c9]Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas:
Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling. ACL (Findings) 2024: 231-247- [c8]Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas:
Visual Grounding Helps Learn Word Meanings in Low-Data Regimes. NAACL-HLT 2024: 1311-1329 - [i12]Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas:
Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling. CoRR abs/2403.14551 (2024) - [i11]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 abs/2404.06214 (2024) - [i10]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 abs/2406.10447 (2024) - 2023
- [j3]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) - [i9]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 abs/2301.11796 (2023) - [i8]Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas:
Visual Grounding Helps Learn Word Meanings in Low-Data Regimes. CoRR abs/2310.13257 (2023) - 2022
- [c7]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 - 2021
- [j2]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): e2014196118 (2021) - [c6]Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman:
Conditional Negative Sampling for Contrastive Learning of Visual Representations. ICLR 2021 - 2020
- [c5]Chengxu Zhuang, Tianwei She, Alex Andonian, Max Sobol Mark, Daniel Yamins:
Unsupervised Learning From Video With Deep Neural Embeddings. CVPR 2020: 9560-9569 - [i7]Mike Wu, Chengxu Zhuang, Milan Mosse, Daniel Yamins, Noah D. Goodman:
On Mutual Information in Contrastive Learning for Visual Representations. CoRR abs/2005.13149 (2020) - [i6]Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman:
Conditional Negative Sampling for Contrastive Learning of Visual Representations. CoRR abs/2010.02037 (2020)
2010 – 2019
- 2019
- [c4]Chengxu Zhuang, Alex Lin Zhai, Daniel Yamins:
Local Aggregation for Unsupervised Learning of Visual Embeddings. ICCV 2019: 6001-6011 - [i5]Chengxu Zhuang, Alex Lin Zhai, Daniel Yamins:
Local Aggregation for Unsupervised Learning of Visual Embeddings. CoRR abs/1903.12355 (2019) - [i4]Chengxu Zhuang, Xuehao Ding, Divyanshu Murli, Daniel Yamins:
Local Label Propagation for Large-Scale Semi-Supervised Learning. CoRR abs/1905.11581 (2019) - [i3]Chengxu Zhuang, Alex Andonian, Daniel Yamins:
Unsupervised Learning from Video with Deep Neural Embeddings. CoRR abs/1905.11954 (2019) - 2018
- [c3]Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Josh Tenenbaum, Daniel L. K. Yamins:
Flexible neural representation for physics prediction. NeurIPS 2018: 8813-8824 - [i2]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 abs/1806.08047 (2018) - 2017
- [j1]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: 100 (2017) - [c2]Chengxu Zhuang, Jonas Kubilius, Mitra J. Z. Hartmann, Daniel Yamins:
Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System. NIPS 2017: 2555-2565 - [i1]Chengxu Zhuang, Jonas Kubilius, Mitra J. Z. Hartmann, Daniel Yamins:
Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System. CoRR abs/1706.07555 (2017) - 2015
- [c1]Mingmin Zhao, Chengxu Zhuang, Yizhou Wang, Tai Sing Lee:
Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction. ICLR (Workshop) 2015
Coauthor Index
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