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ORCIDYao-Xiang Ding 0001
Person information
- affiliation: Zhejiang University, State Key Lab of CAD & CG, China
- affiliation: Nanjing University, National Key Laboratory for Novel Software Technology, China
Other persons with the same name
- Yaoxiang Ding 0002 — Peking University, Speech and Hearing Research Center, Key Lab of Machine Perception, Beijing, China
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2020 – today
- 2025
[j6]Zipei Chen, Yumeng Li, Zhong Ren, Yao-Xiang Ding
, Kun Zhou:
Appearance as reliable evidence: Reconciling appearance and generative priors for monocular motion estimation. Comput. Graph. 132: 104404 (2025)- [j5]Jingming Liu, Yumeng Li, Boyuan Xiao, Yichang Jian, Ziang Qin, Tianjia Shao, Yao-Xiang Ding, Kun Zhou:
Autonomous Imagination: Closed-Loop Decomposition of Visual-to-Textual Conversion in Visual Reasoning for Multimodal Large Language Models. Trans. Mach. Learn. Res. 2025 (2025) - [j4]Yuting Tang, Xin-Qiang Cai, Yao-Xiang Ding, Qiyu Wu, Guoqing Liu, Masashi Sugiyama:
Reinforcement Learning from Bagged Reward. Trans. Mach. Learn. Res. 2025 (2025) - [j3]Lanjihong Ma, Yao-Xiang Ding, Peng Zhao, Zhi-Hua Zhou:
Learning Objective Adaptation by Correlation-Based Model Reuse. IEEE Trans. Neural Networks Learn. Syst. 36(8): 14440-14451 (2025) - [c14]Qing Chang, Yao-Xiang Ding, Kun Zhou:
Enhancing Identity-Deformation Disentanglement in StyleGAN for One-Shot Face Video Re-Enactment. AAAI 2025: 1247-1255 - [c13]Lanjihong Ma, Yao-Xiang Ding, Zhen-Yu Zhang, Zhi-Hua Zhou:
Achieving Nearly-Optimal Regret and Sample Complexity in Dueling Bandits with Applications in Online Recommendations. KDD (1) 2025: 1008-1019 - [c12]Yifei Peng, Zijie Zha, Yu Jin, Zhexu Luo, Wang-Zhou Dai, Zhong Ren, Yao-Xiang Ding, Kun Zhou:
Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings. KDD (2) 2025: 2291-2302 - [c11]Bohong Chen, Yumeng Li, Youyi Zheng, Yao-Xiang Ding, Kun Zhou:
Motion-example-controlled Co-speech Gesture Generation Leveraging Large Language Models. SIGGRAPH (Conference Paper Track) 2025: 55:1-55:12 - [i15]Yu Jin, Jingming Liu, Zhexu Luo, Yifei Peng, Ziang Qin, Wang-Zhou Dai, Yao-Xiang Ding, Kun Zhou:
Pre-Training Meta-Rule Selection Policy for Visual Generative Abductive Learning. CoRR abs/2503.06427 (2025) - [i14]Jingming Liu, Yumeng Li, Wei Shi, Yao-Xiang Ding, Hui Su, Kun Zhou:
Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation. CoRR abs/2506.18670 (2025) - [i13]Bohong Chen, Yumeng Li, Youyi Zheng, Yao-Xiang Ding, Kun Zhou:
Motion-example-controlled Co-speech Gesture Generation Leveraging Large Language Models. CoRR abs/2507.20220 (2025) - [i12]Yifei Peng, Yaoli Liu, Enbo Xia, Yu Jin, Wang-Zhou Dai, Zhong Ren, Yao-Xiang Ding, Kun Zhou:
Abductive Logical Rule Induction by Bridging Inductive Logic Programming and Multimodal Large Language Models. CoRR abs/2509.21874 (2025) - [i11]Yaoli Liu, Yao-Xiang Ding, Kun Zhou:
FreeFuse: Multi-Subject LoRA Fusion via Auto Masking at Test Time. CoRR abs/2510.23515 (2025) - 2024
- [j2]Yumeng Li, Bohong Chen, Zhong Ren, Yao-Xiang Ding, Libin Liu, Tianjia Shao, Kun Zhou:
CPoser: An Optimization-after-Parsing Approach for Text-to-Pose Generation Using Large Language Models. ACM Trans. Graph. 43(6): 196:1-196:13 (2024) - [c10]Yu-Cheng He, Yao-Xiang Ding, Han-Jia Ye, Zhi-Hua Zhou:
Learning Only When It Matters: Cost-Aware Long-Tailed Classification. AAAI 2024: 12411-12420 - [c9]Yu Jin, Jingming Liu, Zhexu Luo, Yifei Peng, Ziang Qin, Wang-Zhou Dai, Yao-Xiang Ding, Kun Zhou:
Pre-Training Meta-Rule Selection Policy for Visual Generative Abductive Learning. IJCLR 2024: 163-180 - [c8]Lanjihong Ma, Zhen-Yu Zhang, Yao-Xiang Ding, Zhi-Hua Zhou:
Handling Varied Objectives by Online Decision Making. KDD 2024: 2130-2140 - [c7]Bohong Chen, Yumeng Li, Yao-Xiang Ding, Tianjia Shao, Kun Zhou:
Enabling Synergistic Full-Body Control in Prompt-Based Co-Speech Motion Generation. ACM Multimedia 2024: 6774-6783 - [i10]Yuting Tang, Xin-Qiang Cai, Yao-Xiang Ding, Qiyu Wu, Guoqing Liu, Masashi Sugiyama:
Reinforcement Learning from Bagged Reward: A Transformer-based Approach for Instance-Level Reward Redistribution. CoRR abs/2402.03771 (2024) - [i9]Bohong Chen, Yumeng Li, Yao-Xiang Ding, Tianjia Shao, Kun Zhou:
Enabling Synergistic Full-Body Control in Prompt-Based Co-Speech Motion Generation. CoRR abs/2410.00464 (2024) - [i8]Yuting Tang, Xin-Qiang Cai, Jing-Cheng Pang, Qiyu Wu, Yao-Xiang Ding, Masashi Sugiyama:
Beyond Simple Sum of Delayed Rewards: Non-Markovian Reward Modeling for Reinforcement Learning. CoRR abs/2410.20176 (2024) - [i7]Jingming Liu, Yumeng Li, Boyuan Xiao, Yichang Jian, Ziang Qin, Tianjia Shao, Yao-Xiang Ding, Kun Zhou:
Enhancing Visual Reasoning with Autonomous Imagination in Multimodal Large Language Models. CoRR abs/2411.18142 (2024) - 2023
- [c6]Xin-Qiang Cai, Yao-Xiang Ding, Zi-Xuan Chen, Yuan Jiang, Masashi Sugiyama, Zhi-Hua Zhou:
Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning. ICLR 2023 - [c5]Yi-Kai Zhang, Ting-Ji Huang, Yao-Xiang Ding, De-Chuan Zhan, Han-Jia Ye:
Model Spider: Learning to Rank Pre-Trained Models Efficiently. NeurIPS 2023 - [i6]Yi-Kai Zhang, Ting-Ji Huang, Yao-Xiang Ding, De-Chuan Zhan, Han-Jia Ye:
Model Spider: Learning to Rank Pre-Trained Models Efficiently. CoRR abs/2306.03900 (2023) - [i5]Yifei Peng, Yu Jin, Zhexu Luo, Yao-Xiang Ding, Wang-Zhou Dai, Zhong Ren, Kun Zhou:
Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings. CoRR abs/2310.17451 (2023) - [i4]Yumeng Li, Yaoxiang Ding, Zhong Ren, Kun Zhou:
QPoser: Quantized Explicit Pose Prior Modeling for Controllable Pose Generation. CoRR abs/2312.01104 (2023) - 2022
- [c4]Yao-Xiang Ding, Xi-Zhu Wu, Kun Zhou, Zhi-Hua Zhou:
Pre-Trained Model Reusability Evaluation for Small-Data Transfer Learning. NeurIPS 2022 - 2021
- [c3]Xin-Qiang Cai, Yao-Xiang Ding, Yuan Jiang, Zhi-Hua Zhou:
Imitation Learning from Pixel-Level Demonstrations by HashReward. AAMAS 2021: 279-287 - [i3]Xin-Qiang Cai, Yao-Xiang Ding, Zi-Xuan Chen, Yuan Jiang, Masashi Sugiyama, Zhi-Hua Zhou:
Seeing Differently, Acting Similarly: Imitation Learning with Heterogeneous Observations. CoRR abs/2106.09256 (2021) - 2020
- [c2]Yao-Xiang Ding, Zhi-Hua Zhou:
Boosting-Based Reliable Model Reuse. ACML 2020: 145-160
2010 – 2019
- 2019
- [i2]Xin-Qiang Cai, Yao-Xiang Ding, Yuan Jiang, Zhi-Hua Zhou:
Expert-Level Atari Imitation Learning from Demonstrations Only. CoRR abs/1909.03773 (2019) - 2018
- [j1]Yao-Xiang Ding, Zhi-Hua Zhou:
Crowdsourcing with unsure option. Mach. Learn. 107(4): 749-766 (2018) - [c1]Yao-Xiang Ding, Zhi-Hua Zhou:
Preference Based Adaptation for Learning Objectives. NeurIPS 2018: 7839-7848 - 2016
- [i1]Yao-Xiang Ding, Zhi-Hua Zhou:
Crowdsourcing with Unsure Option. CoRR abs/1609.00292 (2016)
Coauthor Index
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