Du, Yilun

Improving Factuality and Reasoning in Language Models through Multiagent Debate

Du, Y., Li, S., Torralba, A., Tenenbaum, J. B., & Mordatch, I. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,202

Diffusion policy: Visuomotor policy learning via action diffusion

Chi, C., Xu, Z., Feng, S., Cousineau, E., Du, Y., Burchfiel, B., Tedrake, R., & Song, S. (2025) · The International Journal of Robotics Research

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 613

Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Chi, C., Feng, S., Du, Y., Xu, Z., Cousineau, E., Burchfiel, B., & Song, S. (2023) · Robotics: Science and Systems XIX

Reinforcement Learning in RoboticsMotor Control and Adaptation

Cited by 530

3D Shape Generation and Completion through Point-Voxel Diffusion

Zhou, L., Du, Y., & Wu, J. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

3D Shape Modeling and AnalysisGenerative Adversarial Networks and Image Synthesis

Cited by 421

Learning Interactive Real-World Simulators

Yang, S., Du, Y., Ghasemipour, K., Tompson, J., Kaelbling, L., Schuurmans, D., & Abbeel, P. (2023) · arXiv

Reinforcement Learning in RoboticsMultimodal Machine Learning Applications

Cited by 346

Compositional Visual Generation with Composable Diffusion Models

Liu, N., Li, S., Du, Y., Torralba, A., & Tenenbaum, J. B. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 295

Towards a Science of Scaling Agent Systems

Kim, Y., Gu, K., Park, C., Park, C., Schmidgall, S., Heydari, A. A., Yan, Y., Zhang, Z., Zhuang, Y., Liu, Y., et al. (2025) · arXiv

Multi-Agent Systems and NegotiationAI-based Problem Solving and Planning

Cited by 197

Language models generalize beyond natural proteins

Verkuil, R., Kabeli, O., Du, Y., Wicky, B. I. M., Milles, L. F., Dauparas, J., Baker, D., Ovchinnikov, S., Sercu, T., & Rives, A. (2022) · bioRxiv (Cold Spring Harbor Laboratory)

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 181

Planning with Diffusion for Flexible Behavior Synthesis

Janner, M., Du, Y., Tenenbaum, J. B., & Levine, S. (2022) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 140

3D-LLM: Injecting the 3D World into Large Language Models

Hong, Y., Zhen, H., Chen, P., Zheng, S., Du, Y., Chen, Z., & Gan, C. (2023) · arXiv

Multimodal Machine Learning Applications3D Shape Modeling and Analysis

Cited by 124

Is Conditional Generative Modeling all you need for Decision-Making?

Ajay, A., Du, Y., Gupta, A., Tenenbaum, J., Jaakkola, T., & Agrawal, P. (2022) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 61

Foundation Models for Decision Making: Problems, Methods, and Opportunities

Yang, S., Nachum, O., Du, Y., Wei, J., Abbeel, P., & Schuurmans, D. (2023) · arXiv

Multimodal Machine Learning ApplicationsAI-based Problem Solving and Planning

Cited by 60

Building Cooperative Embodied Agents Modularly with Large Language Models

Zhang, H., Du, W., Shan, J., Zhou, Q., Du, Y., Tenenbaum, J. B., Shu, T., & Gan, C. (2023) · arXiv

Reinforcement Learning in RoboticsMulti-Agent Systems and Negotiation

Cited by 52

Observational Overfitting in Reinforcement Learning

Song, X., Jiang, Y., Tu, S., Du, Y., & Neyshabur, B. (2019) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 48

Improved Contrastive Divergence Training of Energy Based Models

Du, Y., Li, S., Tenenbaum, J., & Mordatch, I. (2020) · arXiv

Generative Adversarial Networks and Image SynthesisAdversarial Robustness in Machine Learning

Cited by 36

3D-VLA: A 3D Vision-Language-Action Generative World Model

Zhen, H., Qiu, X., Chen, P., Yang, J., Yan, X., Du, Y., Hong, Y., & Gan, C. (2024) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 15

Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Chi, C., Xu, Z., Feng, S., Cousineau, E., Du, Y., Burchfiel, B., Tedrake, R., & Song, S. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 12

Gemini Robotics: Bringing AI into the Physical World

Gemini Robotics Team, Abeyruwan, S., Ainslie, J., Alayrac, J.-B., Arenas, M. G., Armstrong, T., Balakrishna, A., Baruch, R., Bauza, M., Blokzijl, M., et al. (2025) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 8

Grading Scale Impact on LLM-as-a-Judge: Human-LLM Alignment Is Highest on 0-5 Grading Scale

Li, W., Zhao, M., Dong, W., Cai, J., Wei, Y., Pocress, M., Li, Y., Yuan, W., Wang, X., Hou, R., et al. (2026) · arXiv

Reliability and Agreement in MeasurementNatural Language Processing Techniques

Cited by 4

RoboDreamer: Learning Compositional World Models for Robot Imagination

Zhou, S., Du, Y., Chen, J., Li, Y., Yeung, D.-Y., & Gan, C. (2024) · arXiv

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 4

Learning to Act from Actionless Videos through Dense Correspondences

Ko, P.-C., Mao, J., Du, Y., Sun, S.-H., & Tenenbaum, J. B. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 3

Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains

Subramaniam, V., Du, Y., Tenenbaum, J. B., Torralba, A., Li, S., & Mordatch, I. (2025) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 2

Energy-Based Transformers are Scalable Learners and Thinkers

Gladstone, A., Nanduru, G., Islam, M. M., Han, P., Ha, H., Chadha, A., Du, Y., Ji, H., Li, J., & Iqbal, T. (2025) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 1

Solving New Tasks by Adapting Internet Video Knowledge

Luo, C., Zeng, Z., Du, Y., & Sun, C. (2025) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 0