Chengxu Zhuang

27 papers A* 5B 1Journal 17Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora. CoRR Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Wilcox, Chengxu Zhuang, Juan Ciro, Rafael Mosquera, Bhargavi Paranjape, Adina Williams, Tal Linzen, Ryan Cotterell
2024	J	`jnl`	Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora. CoRR Michael Y. Hu, Aaron Mueller, Candace Ross, Adina Williams, Tal Linzen, Chengxu Zhuang, Ryan Cotterell, Leshem Choshen, Alex Warstadt, Ethan Gotlieb Wilcox
2024	B	`conf`	Insights from the first BabyLM Challenge: Training sample-efficient language models on a developmentally plausible corpus. CogSci Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Gotlieb Wilcox, Chengxu Zhuang, Adina Williams, Ryan Cotterell, Tal Linzen
2024	—	`conf`	Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling. ACL (Findings) Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
2024	J	`jnl`	Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling. CoRR Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
2024	J	`jnl`	The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiences. CoRR Bria Long, Violet Xiang, Stefan Stojanov, Robert Z. Sparks, Zi Yin, Grace E. Keene, Alvin Wei Ming Tan, Steven Y. Feng, Chengxu Zhuang, Virginia A. Marchman, Daniel L. K. Yamins, Michael C. Frank
2024	—	`conf`	Visual Grounding Helps Learn Word Meanings in Low-Data Regimes. NAACL-HLT Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
2024	J	`jnl`	[Call for Papers] The 2nd BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus. CoRR Leshem Choshen, Ryan Cotterell, Michael Y. Hu, Tal Linzen, Aaron Mueller, Candace Ross, Alex Warstadt, Ethan Wilcox, Adina Williams, Chengxu Zhuang
2023	J	`jnl`	Call for Papers - The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus. CoRR Alex Warstadt, Leshem Choshen, Aaron Mueller, Adina Williams, Ethan Wilcox, Chengxu Zhuang
2023	J	`jnl`	Mouse visual cortex as a limited resource system that self-learns an ecologically-general representation. PLoS Comput. Biol. Aran Nayebi, Nathan C. L. Kong, Chengxu Zhuang, Justin L. Gardner, Anthony M. Norcia, Daniel L. K. Yamins
2023	J	`jnl`	Visual Grounding Helps Learn Word Meanings in Low-Data Regimes. CoRR Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
2022	A*	`conf`	How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning? NeurIPS Chengxu Zhuang, Ziyu Xiang, Yoon Bai, Xiaoxuan Jia, Nicholas B. Turk-Browne, Kenneth A. Norman, James J. DiCarlo, Dan Yamins
2021	A*	`conf`	Conditional Negative Sampling for Contrastive Learning of Visual Representations. ICLR Mike Wu, Milan Mossé, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
2021	J	`jnl`	Unsupervised neural network models of the ventral visual stream. Proc. Natl. Acad. Sci. USA Chengxu Zhuang, Siming Yan, Aran Nayebi, Martin Schrimpf, Michael C. Frank, James J. DiCarlo, Daniel L. K. Yamins
2020	J	`jnl`	Conditional Negative Sampling for Contrastive Learning of Visual Representations. CoRR Mike Wu, Milan Mossé, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
2020	J	`jnl`	On Mutual Information in Contrastive Learning for Visual Representations. CoRR Mike Wu, Chengxu Zhuang, Milan Mossé, Daniel Yamins, Noah D. Goodman
2020	A*	`conf`	Unsupervised Learning From Video With Deep Neural Embeddings. CVPR Chengxu Zhuang, Tianwei She, Alex Andonian, Max Sobol Mark, Daniel Yamins
2019	A*	`conf`	Local Aggregation for Unsupervised Learning of Visual Embeddings. ICCV Chengxu Zhuang, Alex Lin Zhai, Daniel Yamins
2019	J	`jnl`	Local Aggregation for Unsupervised Learning of Visual Embeddings. CoRR Chengxu Zhuang, Alex Lin Zhai, Daniel Yamins
2019	J	`jnl`	Local Label Propagation for Large-Scale Semi-Supervised Learning. CoRR Chengxu Zhuang, Xuehao Ding, Divyanshu Murli, Daniel Yamins
2019	J	`jnl`	Unsupervised Learning from Video with Deep Neural Embeddings. CoRR Chengxu Zhuang, Alex Andonian, Daniel Yamins
2018	J	`jnl`	Flexible Neural Representation for Physics Prediction. CoRR Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Joshua B. Tenenbaum, Daniel L. K. Yamins
2018	A*	`conf`	Flexible neural representation for physics prediction. NeurIPS Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Josh Tenenbaum, Daniel L. K. Yamins
2017	J	`jnl`	Deep Learning Predicts Correlation between a Functional Signature of Higher Visual Areas and Sparse Firing of Neurons. Frontiers Comput. Neurosci. Chengxu Zhuang, Yulong Wang, Daniel Yamins, Xiaolin Hu
2017	—	`conf`	Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System. NIPS Chengxu Zhuang, Jonas Kubilius, Mitra J. Z. Hartmann, Daniel Yamins
2017	J	`jnl`	Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System. CoRR Chengxu Zhuang, Jonas Kubilius, Mitra J. Z. Hartmann, Daniel Yamins
2015	—	`conf`	Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction. ICLR (Workshop) Mingmin Zhao, Chengxu Zhuang, Yizhou Wang, Tai Sing Lee