Yu Yao

According to our database, Yu Yao authored at least 25 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

SmartCLIP: Modular Vision-language Alignment with Identification Guarantees.

Shaoan Xie, Lingjing Kong, Yujia Zheng, Yu Yao, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang

CoRR, July, 2025

A Sample Efficient Conditional Independence Test in the Presence of Discretization.

Boyang Sun, Yu Yao, Xinshuai Dong, Zongfang Liu, Tongliang Liu, Yumou Qiu, Kun Zhang

CoRR, June, 2025

Beyond Optimal Transport: Model-Aligned Coupling for Flow Matching.

Yexiong Lin, Yu Yao, Tongliang Liu

CoRR, May, 2025

Flow: A Modular Approach to Automated Agentic Workflow Generation.

Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao, Kun Zhang, Tongliang Liu

CoRR, January, 2025

Chain-of-Focus Prompting: Leveraging Sequential Visual Cues to Prompt Large Autoregressive Vision Models.

Jiyang Zheng, Jialiang Shen, Yu Yao, Min Wang, Yang Yang, Dadong Wang, Tongliang Liu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

A Robust Method to Discover Causal or Anticausal Relation.

Yu Yao, Yang Zhou, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Flow: Modularized Agentic Workflow Automation.

Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao, Kun Zhang, Tongliang Liu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

SmartCLIP: Modular Vision-language Alignment with Identification Guarantees.

Shaoan Xie, Lingjing, Yujia Zheng, Yu Yao, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

ProtoSimi: label correction for fine-grained visual categorization.

Jialiang Shen, Yu Yao, Shaoli Huang, Zhiyong Wang, Jing Zhang, Ruxing Wang, Jun Yu, Tongliang Liu

Mach. Learn., April, 2024

Ranked from Within: Ranking Large Multimodal Models for Visual Question Answering Without Labels.

Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng, Tom Gedeon, Tongliang Liu

CoRR, 2024

Identifying Latent State-Transition Processes for Individualized Reinforcement Learning.

Yuewen Sun, Biwei Huang, Yu Yao, Donghuo Zeng, Xinshuai Dong, Songyao Jin, Boyang Sun, Roberto Legaspi, Kazushi Ikeda, Peter Spirtes, Kun Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Learning the Latent Causal Structure for Modeling Label Noise.

Yexiong Lin, Yu Yao, Tongliang Liu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation.

Jiyang Zheng, Yu Yao, Bo Han, Dadong Wang, Tongliang Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Improving Non-Transferable Representation Learning by Harnessing Content and Style.

Ziming Hong, Zhenyi Wang, Li Shen, Yu Yao, Zhuo Huang, Shiming Chen, Chuanwu Yang, Mingming Gong, Tongliang Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Trustworthy and Responsible AI for Information and Knowledge Management System.

Huaming Chen, Jun Zhuang, Yu Yao, Wei Jin, Haohan Wang, Yong Xie, Chi-Hung Chi, Kim-Kwang Raymond Choo

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos.

Lianyang Ma, Yu Yao, Tao Liang, Tongliang Liu

Proceedings of the AI 2024: Advances in Artificial Intelligence, 2024

2023

Understanding How Pretraining Regularizes Deep Learning Algorithms.

Yu Yao, Baosheng Yu, Chen Gong, Tongliang Liu

IEEE Trans. Neural Networks Learn. Syst., September, 2023

CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation.

Yexiong Lin, Yu Yao, Xiaolong Shi, Mingming Gong, Xu Shen, Dong Xu, Tongliang Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions.

Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du, Dacheng Tao

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?

Yu Yao, Mingming Gong, Yuxuan Du, Jun Yu, Bo Han, Kun Zhang, Tongliang Liu

Proceedings of the International Conference on Machine Learning, 2023

2022

Do We Need to Penalize Variance of Losses for Learning with Label Noise?

Yexiong Lin, Yu Yao, Yuxuan Du, Jun Yu, Bo Han, Mingming Gong, Tongliang Liu

CoRR, 2022

Rethinking Class-Prior Estimation for Positive-Unlabeled Learning.

Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Instance-dependent Label-noise Learning under a Structural Causal Model.

Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Towards Mixture Proportion Estimation without Irreducibility.

Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao

CoRR, 2020

Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning.

Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020