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ORCIDYangjun Ruan
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2020 – today
- 2024
[c7]Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto:
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. ICLR 2024- [i9]Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto:
Observational Scaling Laws and the Predictability of Language Model Performance. CoRR abs/2405.10938 (2024) - [i8]Honghua Dong, Qidong Su, Yubo Gao, Zhaoyu Li, Yangjun Ruan, Gennady Pekhimenko, Chris J. Maddison, Xujie Si:
APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts. CoRR abs/2406.13161 (2024) - 2023
- [c6]Yangjun Ruan, Saurabh Singh, Warren Richard Morningstar, Alexander A. Alemi, Sergey Ioffe, Ian Fischer, Joshua V. Dillon:
Weighted Ensemble Self-Supervised Learning. ICLR 2023 - [i7]Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto:
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. CoRR abs/2309.15817 (2023) - 2022
- [c5]Yangjun Ruan, Yann Dubois, Chris J. Maddison:
Optimal Representations for Covariate Shift. ICLR 2022 - [c4]Haonan Duan, Pashootan Vaezipoor, Max B. Paulus, Yangjun Ruan, Chris J. Maddison:
Augment with Care: Contrastive Learning for Combinatorial Problems. ICML 2022: 5627-5642 - [i6]Yangjun Ruan, Yann Dubois, Chris J. Maddison:
Optimal Representations for Covariate Shift. CoRR abs/2201.00057 (2022) - [i5]Haonan Duan, Pashootan Vaezipoor, Max B. Paulus, Yangjun Ruan, Chris J. Maddison:
Augment with Care: Contrastive Learning for the Boolean Satisfiability Problem. CoRR abs/2202.08396 (2022) - [i4]Yangjun Ruan, Saurabh Singh, Warren R. Morningstar, Alexander A. Alemi, Sergey Ioffe, Ian Fischer, Joshua V. Dillon:
Weighted Ensemble Self-Supervised Learning. CoRR abs/2211.09981 (2022) - 2021
- [c3]Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison:
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. ICML 2021: 9136-9147 - [i3]Yangjun Ruan, Karen Ullrich, Daniel Severo
, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison:
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. CoRR abs/2102.11086 (2021) - 2020
- [c2]Yangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, Cho-Jui Hsieh:
Learning to Learn by Zeroth-Order Oracle. ICLR 2020
2010 – 2019
- 2019
- [j1]Jinke Ren, Yangjun Ruan, Guanding Yu:
Data Transmission in Mobile Edge Networks: Whether and Where to Compress? IEEE Commun. Lett. 23(3): 490-493 (2019) - [c1]Yi Ren, Yangjun Ruan, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
FastSpeech: Fast, Robust and Controllable Text to Speech. NeurIPS 2019: 3165-3174 - [i2]Yi Ren, Yangjun Ruan, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu:
FastSpeech: Fast, Robust and Controllable Text to Speech. CoRR abs/1905.09263 (2019) - [i1]Yangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, Cho-Jui Hsieh:
Learning to Learn by Zeroth-Order Oracle. CoRR abs/1910.09464 (2019)
Coauthor Index
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