Gu, Shixiang

Categorical Reparameterization with Gumbel-Softmax

Jang, E., Gu, S., & Poole, B. (2016) · arXiv

Topic ModelingGaussian Processes and Bayesian Inference

Cited by 3,616

Scaling Instruction-Finetuned Language Models

Chung, H. W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., Li, Y., Wang, X., Dehghani, M., Brahma, S., et al. (2022) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1,441

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

Data-efficient hierarchical reinforcement learning

Nachum, O., Gu, S., Lee, H., & Levine, S. (2018) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 446

Large Language Models Can Self-Improve

Huang, J., Gu, S. S., Hou, L., Wu, Y., Wang, X., Yu, H., & Han, J. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 230

Large Language Models Can Self-Improve

Huang, J., Gu, S., Hou, L., Wu, Y., Wang, X., Yu, H., & Han, J. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 230

Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog

Jaques, N., Ghandeharioun, A., Shen, J. H., Ferguson, C., Lapedriza, A., Jones, N., Gu, S., & Picard, R. (2019) · arXiv

Reinforcement Learning in RoboticsSpeech and dialogue systems

Cited by 126

Multimodal Web Navigation with Instruction-Finetuned Foundation Models

Furuta, H., Lee, K.-H., Nachum, O., Matsuo, Y., Faust, A., Gu, S. S., & Gur, I. (2023) · arXiv

Web Data Mining and AnalysisInformation Retrieval and Search Behavior

Cited by 115

Language as an Abstraction for Hierarchical Deep Reinforcement Learning

Jiang, Y., Gu, S., Murphy, K., & Finn, C. (2019) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 109

Multi-agent manipulation via locomotion using hierarchical sim2real

Nachum, O., Ahn, M., Ponte, H., Gu, S., & Kumar, V. (2019) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 46

Mind's Eye: Grounded Language Model Reasoning through Simulation

Liu, R., Wei, J., Gu, S. S., Wu, T.-Y., Vosoughi, S., Cui, C., Zhou, D., & Dai, A. M. (2022) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 24