Wu, Yuhuai

Grandmaster level in StarCraft II using multi-agent reinforcement learning

Vinyals, O., Babuschkin, I., Czarnecki, W. M., Mathieu, M., Dudzik, A., Chung, J., Choi, D. H., Powell, R., Ewalds, T., Georgiev, P., et al. (2019) · Nature

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 3,455

On the Opportunities and Risks of Foundation Models

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 2,676

PaLM 2 Technical Report

Anil, R., Dai, A. M., Firat, O., Johnson, M., Lepikhin, D., Passos, A., Shakeri, S., Taropa, E., Bailey, P., Chen, Z., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 834

Solving olympiad geometry without human demonstrations

Trinh, T. H., Wu, Y., Le, Q. V., He, H., & Luong, T. (2024) · Nature

AI-based Problem Solving and PlanningArtificial Intelligence Applications

Cited by 311

Holistic Evaluation of Language Models

Liang, P., Bommasani, R., Lee, T., Tsipras, D., Soylu, D., Yasunaga, M., Zhang, Y., Narayanan, D., Wu, Y., Kumar, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 255

Memorizing Transformers

Wu, Y., Rabe, M. N., Hutchins, D., & Szegedy, C. (2022) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 90

Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference

Roeder, G., Wu, Y., & Duvenaud, D. (2017) · arXiv

Gaussian Processes and Bayesian InferenceMarkov Chains and Monte Carlo Methods

Cited by 84

Length Generalization in Arithmetic Transformers

Jelassi, S., d'Ascoli, S., Domingo-Enrich, C., Wu, Y., Li, Y., & Charton, F. (2023) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 76

Some Considerations on Learning to Explore via Meta-Reinforcement Learning

Stadie, B. C., Yang, G., Houthooft, R., Chen, X., Duan, Y., Wu, Y., Abbeel, P., & Sutskever, I. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 74

Exploring Length Generalization in Large Language Models

Anil, C., Wu, Y., Andreassen, A., Lewkowycz, A., Misra, V., Ramasesh, V., Slone, A., Gur-Ari, G., Dyer, E., & Neyshabur, B. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 44

INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving

Wu, Y., Jiang, A. Q., Ba, J., & Grosse, R. (2020) · arXiv

AI-based Problem Solving and PlanningLogic, programming, and type systems

Cited by 30

Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers

Jiang, A. Q., Li, W., Tworkowski, S., Czechowski, K., Odrzygóźdź, T., Miłoś, P., Wu, Y., & Jamnik, M. (2022) · arXiv

Logic, programming, and type systemsMathematics, Computing, and Information Processing

Cited by 23

Language Model Cascades

Dohan, D., Xu, W., Lewkowycz, A., Austin, J., Bieber, D., Lopes, R. G., Wu, Y., Michalewski, H., Saurous, R. A., Sohl-dickstein, J., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 22

Proof Artifact Co-training for Theorem Proving with Language Models

Han, J. M., Rute, J., Wu, Y., Ayers, E. W., & Polu, S. (2021) · arXiv

Logic, programming, and type systemsMathematics, Computing, and Information Processing

Cited by 21

Learning to Give Checkable Answers with Prover-Verifier Games

Anil, C., Zhang, G., Wu, Y., & Grosse, R. (2021) · arXiv

Game Theory and ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 0