Yunke Wang

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I am a Postdoctoral Research Associate at the University of Sydney, working with Prof. Chang Xu. My research spans Embodied AI, Generative Models, and Reinforcement Learning. I work on vision-language-action (VLA) models, world-action models, and whole-body control for embodied agents; image & video generation, editing, and efficient inference; and imitation learning from imperfect demonstrations with adversarial training. I received my Ph.D. from Wuhan University (2024) advised by Prof. Bo Du.

News

• (2026.06) 1 paper is accepted by ECCV 2026.
• (2026.05) I will serve as the Web Chair of ACM MM 2027 [CORE A*].
• (2026.05) I received Gold Reviewer Award at ICML 2026.
• (2026.05) We received an ARC Linkage Project (LP) grant on "Enabling VLA Assistive Robotics for the Future of Aged Care in Australia"!
• (2026.05) I will serve as the Area Chair of NeurIPS 2026.
• (2026.05) I will serve as the Local Arrangement Chair of DICTA 2026 [Australia's premier conference on computer vision].
• (2026.05) 1 paper is accepted by TIP 2026 (IF 10.8).
• (2026.05) 4 papers are accepted by ICML 2026.
• (2026.04) 1 paper is accepted by ACL 2026.
• (2026.03) I received EMCRs Training Scheme Award as the Lead Applicant, The University of Sydney.
• (2026.02) 3 papers (1 Highlight) are accepted by CVPR 2026.
• (2026.01) We received an AEA (Australia's Economic Accelerator) Ignite grant on "Last-link Automation in Daily Retail Operations"!
• (2026.01) 1 paper is accepted by ICLR 2026.
• (2025.11) 1 paper is accepted by AAAI 2026.
• (2025.09) 1 paper is accepted by NeurIPS 2025.
• (2025.05) 1 paper is accepted by TPAMI 2025 (IF 20.4).
• (2025.05) 1 paper is accepted by ICML 2025.
• (2025.05) 1 paper is accepted by KDD 2025.
• (2025.05) Successfully organized the Workshop on Sustainable AI for the Future Web at The Web Conference 2025 [CORE A*], Sydney, Australia.

Selected Publications

• TPAMI 2025
  [1] On Positive-Unlabeled Classification from Corrupted Data in GANs

  Yunke Wang, Chang Xu, Tianyu Guo, Bo Du, Dacheng Tao

  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.

  Core A*CCF AIF 20.4 Paper
• ICML 2025
  [2] Position: AI Scaling: From Up to Down and Out

  Yunke Wang, Yanxi Li, Chang Xu

  International Conference on Machine Learning (ICML), 2025.

  Core A*CCF A Paper News
• ICML 2024
  [3] Imitation Learning from Purified Demonstrations

  Yunke Wang, Minjing Dong, Yukun Zhao, Bo Du, Chang Xu

  International Conference on Machine Learning (ICML), 2024.

  Core A*CCF A Paper Code
• NN 2024
  [4] Multi-Tailed Vision Transformer for Efficient Inference

  Yunke Wang, Bo Du, Wenyuan Wang, Chang Xu

  Neural Networks, 2024.

  Core ACCF BIF 6.0 Paper
• KDD 2023
  [5] Learning to Schedule in Diffusion Probabilistic Models

  Yunke Wang, Xiyu Wang, Anh-Dung Dinh, Bo Du, Chang Xu

  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.

  Core A*CCF A Paper
• AAAI 2023
  [6] Unlabeled Imperfect Demonstrations in Adversarial Imitation Learning

  Yunke Wang, Bo Du, Chang Xu

  AAAI Conference on Artificial Intelligence (AAAI), 2023.

  Core A*CCF A Paper Supp Code
• IJCAI 2021
  [7] Robust Adversarial Imitation Learning via Adaptively-Selected Demonstrations

  Yunke Wang, Chang Xu, Bo Du

  International Joint Conference on Artificial Intelligence (IJCAI), 2021.

  Core A*CCF A Paper Supp Code
• ICML 2021
  [8] Learning to Weight Imperfect Demonstrations

  Yunke Wang, Chang Xu, Bo Du, Honglak Lee

  International Conference on Machine Learning (ICML), 2021.

  Core A*CCF A Paper Supp Code Code (Atari)
• Preprint
  [9] Visual Imitation Learning with Calibrated Contrastive Representation

  Yunke Wang, Linwei Tao, Yutian Lin, Bo Du, Chang Xu

  Preprint, 2024.

  Paper

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