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ORCIDYu Yao 0005
Person information
- affiliation: University of Sydney, School of Computer Science, Sydney, Australia
- affiliation: Mohamed bin Zayed University of Artificial Intelligence, Department of Machine Learning, Masdar City, Abu Dhabi
- affiliation: Carnegie Mellon University, Pittsburgh, PA, USA
- affiliation (PhD 2023): University of Sydney, School of Computer Science, Sydney, Australia
Other persons with the same name
- Yao Yu (aka: Yu Yao) — disambiguation page
- Yu Yao 0001
![[0000-0002-7282-491X]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-7282-491X")
— Hainan University, School of Information and Communication Engineering, Haikou, China (and 3 more) - Yu Yao 0002 — Northeastern University, School of Computer Science and Engineering, Shenyang, China (and 1 more)
- Yu Yao 0003 — University of Plymouth, School of Engineering, Computing and Mathematics, Plymouth, UK (and 1 more)
- Yu Yao 0004 — Harbin Institute of Technology, School of Astronautics, Harbin, China (and 1 more)
- Yu Yao 0006 — University of Michigan, Robotics Institute, Ann Arbor, MI, USA
- Yu Yao 0007 — Southeast University, School of Electrical and Automation Engineering, Nanjing, China
- Yu Yao 0008 — Southeast University, School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Nanjing, China (and 1 more)
- Yu Yao 0009 — Northeastern University, College of Information Science and Engineering, Shenyang, China (and 1 more)
Other persons with a similar name
- Yao-Yu Wang
- Chia-Yu Yao
- Hongyu Yao (aka: Hong-Yu Yao) — disambiguation page
- Yu-Dong Yao (aka: Yudong Yao, Yu Dong Yao) — Stevens Institute of Technology, Department of Electrical and Computer Engineering, Hoboken, NJ, USA (and 2 more)
- Yue Yao — disambiguation page
- Yao Yu 0001 — Nanjing University, School of Electronic Science and Engineering, Nanjing, China
- Yao Yu 0002 — Northeastern University, School of Computer Science and Engineering, Key Laboratory of Intelligent Computing in Medical Image, Shenyang, China
- Yao Yu 0003 — University of Science and Technology Beijing, School of Intelligence Science and Technology, Beijing, China (and 1 more)
- Yao Yu 0004 — Metawave Co., Carlsbad, CA, USA (and 3 more)
- Yao Yue
- show all similar names
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2020 – today
- 2026
[i17]Yicheng Cao, Zhuo Huang, Yu Yao, Yiming Ying, Daoyi Dong, Tongliang Liu:
i-PhysGaussian: Implicit Physical Simulation for 3D Gaussian Splatting. CoRR abs/2602.17117 (2026)- [i16]Zhenlin Xu, Xiaogang Zhu, Yu Yao, Minhui Xue, Yiliao Song:
From Storage to Steering: Memory Control Flow Attacks on LLM Agents. CoRR abs/2603.15125 (2026) - [i15]Jingyu Guo, Ziye Chen, Ziwen Li, Zhengqing Gao, Jiaxin Huang, Hanlue Zhang, Fengming Huang, Yu Yao, Tongliang Liu, Mingming Gong:
HUGE-Bench: A Benchmark for High-Level UAV Vision-Language-Action Tasks. CoRR abs/2603.19822 (2026) - [i14]Yexiong Lin, Jia Shi, Shanshan Ye, Wanyu Wang, Yu Yao, Tongliang Liu:
SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation. CoRR abs/2604.12273 (2026) - [i13]Shihao Qi, Jie Ma, Rui Xing, Wei Guo, Xiao Huang, Zhitao Gao, Jianhao Deng, Jun Liu, Lingling Zhang, Bifan Wei, Boqian Yang, Pinghui Wang, Jianwen Sun, Jing Tao, Yaqiang Wu, Hui Liu, Yu Yao, Tongliang Liu:
Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems. CoRR abs/2605.14892 (2026) - 2025
- [j3]Yexiong Lin, Yu Yao, Zhaoqing Wang, Xu Shen, Jun Yu, Bo Han, Tongliang Liu:
Improving the Instance-Dependent Transition Matrix Estimation by Exploiting Self-Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. 47(11): 10848-10861 (2025) - [c20]Shaoan Xie, Lingjing, Yujia Zheng, Yu Yao, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang:
SmartCLIP: Modular Vision-language Alignment with Identification Guarantees. CVPR 2025: 29780-29790 - [c19]Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao, Kun Zhang, Tongliang Liu:
Flow: Modularized Agentic Workflow Automation. ICLR 2025 - [c18]Yu Yao, Yang Zhou, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu:
A Robust Method to Discover Causal or Anticausal Relation. ICLR 2025 - [c17]Jiyang Zheng, Jialiang Shen, Yu Yao, Min Wang, Yang Yang, Dadong Wang, Tongliang Liu:
Chain-of-Focus Prompting: Leveraging Sequential Visual Cues to Prompt Large Autoregressive Vision Models. ICLR 2025 - [c16]Ruo-Jing Dong, Yu Yao, Bo Han, Tongliang Liu:
A Lens into Interpretable Transformer Mistakes via Semantic Dependency. ICML 2025 - [c15]Boyang Sun, Yu Yao, Xinshuai Dong, Zongfang Liu, Tongliang Liu, Yumou Qiu, Kun Zhang:
A Sample Efficient Conditional Independence Test in the Presence of Discretization. ICML 2025 - [c14]Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng, Tom Gedeon, Tongliang Liu:
Ranked from Within: Ranking Large Multimodal Models Without Labels. ICML 2025 - [c13]Jiyang Zheng, Siqi Pan, Yu Yao, Zhaoqing Wang, Dadong Wang, Tongliang Liu:
Aligning What Matters: Masked Latent Adaptation for Text-to-Audio-Video Generation. NeurIPS 2025 - [i12]Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao, Kun Zhang, Tongliang Liu:
Flow: A Modular Approach to Automated Agentic Workflow Generation. CoRR abs/2501.07834 (2025) - [i11]Yexiong Lin, Yu Yao, Tongliang Liu:
Beyond Optimal Transport: Model-Aligned Coupling for Flow Matching. CoRR abs/2505.23346 (2025) - [i10]Boyang Sun, Yu Yao, Xinshuai Dong, Zongfang Liu, Tongliang Liu, Yumou Qiu, Kun Zhang:
A Sample Efficient Conditional Independence Test in the Presence of Discretization. CoRR abs/2506.08747 (2025) - [i9]Shaoan Xie, Lingjing Kong, Yujia Zheng, Yu Yao, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang:
SmartCLIP: Modular Vision-language Alignment with Identification Guarantees. CoRR abs/2507.22264 (2025) - [i8]Jialiang Shen, Jiyang Zheng, Yunqi Xue, Huajie Chen, Yu Yao, Hui Kang, Ruiqi Liu, Helin Gong, Yang Yang, Dadong Wang, Tongliang Liu:
DINO-Detect: A Simple yet Effective Framework for Blur-Robust AI-Generated Image Detection. CoRR abs/2511.12511 (2025) - 2024
- [j2]Jialiang Shen, Yu Yao, Shaoli Huang, Zhiyong Wang, Jing Zhang, Ruxing Wang, Jun Yu, Tongliang Liu:
ProtoSimi: label correction for fine-grained visual categorization. Mach. Learn. 113(4): 1903-1920 (2024) - [c12]Lianyang Ma, Yu Yao, Tao Liang, Tongliang Liu:
Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos. AI (2) 2024: 281-297 - [c11]Huaming Chen, Jun Zhuang, Yu Yao, Wei Jin, Haohan Wang, Yong Xie, Chi-Hung Chi, Kim-Kwang Raymond Choo:
Trustworthy and Responsible AI for Information and Knowledge Management System. CIKM 2024: 5574-5576 - [c10]Ziming Hong, Zhenyi Wang, Li Shen, Yu Yao, Zhuo Huang, Shiming Chen, Chuanwu Yang, Mingming Gong, Tongliang Liu:
Improving Non-Transferable Representation Learning by Harnessing Content and Style. ICLR 2024 - [c9]Jiyang Zheng, Yu Yao, Bo Han, Dadong Wang, Tongliang Liu:
Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation. ICLR 2024 - [c8]Yexiong Lin, Yu Yao, Tongliang Liu:
Learning the Latent Causal Structure for Modeling Label Noise. NeurIPS 2024 - [c7]Yuewen Sun, Biwei Huang, Yu Yao, Donghuo Zeng, Xinshuai Dong, Songyao Jin, Boyang Sun, Roberto Legaspi, Kazushi Ikeda, Peter Spirtes, Kun Zhang:
Identifying Latent State-Transition Processes for Individualized Reinforcement Learning. NeurIPS 2024 - [i7]Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng, Tom Gedeon, Tongliang Liu:
Ranked from Within: Ranking Large Multimodal Models for Visual Question Answering Without Labels. CoRR abs/2412.06461 (2024) - 2023
- [j1]Yu Yao, Baosheng Yu, Chen Gong, Tongliang Liu:
Understanding How Pretraining Regularizes Deep Learning Algorithms. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5828-5840 (2023) - [c6]Yu Yao, Mingming Gong, Yuxuan Du, Jun Yu, Bo Han, Kun Zhang, Tongliang Liu:
Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise? ICML 2023: 39660-39673 - [c5]Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du, Dacheng Tao:
PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions. ACM Multimedia 2023: 1924-1932 - [c4]Yexiong Lin, Yu Yao, Xiaolong Shi, Mingming Gong, Xu Shen, Dong Xu, Tongliang Liu:
CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation. NeurIPS 2023 - [i6]Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du, Dacheng Tao:
PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions. CoRR abs/2307.14070 (2023) - 2022
- [c3]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao:
Rethinking Class-Prior Estimation for Positive-Unlabeled Learning. ICLR 2022 - [i5]Yexiong Lin, Yu Yao, Yuxuan Du, Jun Yu, Bo Han, Mingming Gong, Tongliang Liu:
Do We Need to Penalize Variance of Losses for Learning with Label Noise? CoRR abs/2201.12739 (2022) - [i4]Lianyang Ma, Yu Yao, Tao Liang, Tongliang Liu:
Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos. CoRR abs/2206.07981 (2022) - 2021
- [c2]Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang:
Instance-dependent Label-noise Learning under a Structural Causal Model. NeurIPS 2021: 4409-4420 - [i3]Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang:
Instance-dependent Label-noise Learning under a Structural Causal Model. CoRR abs/2109.02986 (2021) - 2020
- [c1]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama:
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning. NeurIPS 2020 - [i2]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao:
Towards Mixture Proportion Estimation without Irreducibility. CoRR abs/2002.03673 (2020) - [i1]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama:
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning. CoRR abs/2006.07805 (2020)
Coauthor Index
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