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ORCIDXiao-Ming Wu 0003
Xiaoming Wu 0003
Person information
- affiliation: Hong Kong Polytechnic University, Department of Computing, Hong Kong
Other persons with the same name
- Xiao-Ming Wu (aka: Xiaoming Wu, Xiao Ming Wu) — disambiguation page
- Xiao-Ming Wu 0001 (aka: Xiaoming Wu 0001) — Tsinghua University, Institute of Microelectronics, Beijing, China
- Xiao-Ming Wu 0002
![[0000-0003-1115-8551]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-1115-8551")
— Sun Yat-sen University, School of Computer Science and Engineering, China (and 1 more)
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Books and Theses
- 2016
[b1]Xiaoming Wu:
Learning on Graphs with Partially Absorbing Random Walks: Theory and Practice. Columbia University, USA, 2016
Journal Articles
- 2023
- [j9]Quanyu Dai, Xiao-Ming Wu, Jiaren Xiao, Xiao Shen, Dan Wang:
Graph Transfer Learning via Adversarial Domain Adaptation With Graph Convolution. IEEE Trans. Knowl. Data Eng. 35(5): 4908-4922 (2023) - [j8]Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu, Xianchao Zhang:
Adaptive Graph Convolution Methods for Attributed Graph Clustering. IEEE Trans. Knowl. Data Eng. 35(12): 12384-12399 (2023) - [j7]Bo Liu, Li-Ming Zhan, Li Xu, Xiao-Ming Wu:
Medical Visual Question Answering via Conditional Reasoning and Contrastive Learning. IEEE Trans. Medical Imaging 42(5): 1532-1545 (2023) - 2022
- [j6]Cong Wang, Honghe Zhu, Wanshu Fan, Xiao-Ming Wu, Junyang Chen:
Single image rain removal using recurrent scale-guide networks. Neurocomputing 467: 242-255 (2022) - [j5]Zhen Peng, Yixiang Dong, Minnan Luo, Xiao-Ming Wu, Qinghua Zheng:
A new self-supervised task on graphs: Geodesic distance prediction. Inf. Sci. 607: 1195-1210 (2022) - [j4]Quanyu Dai, Xiao-Ming Wu, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Dan Wang, Guli Lin, Keping Yang:
Personalized knowledge-aware recommendation with collaborative and attentive graph convolutional networks. Pattern Recognit. 128: 108628 (2022) - [j3]Junyang Chen, Zhiguo Gong, Yuanman Li, Huanjian Zhang, Hongyong Yu, Junzhang Zhu, Ge Fan, Xiao-Ming Wu, Kaishun Wu:
Meta-Path Based Neighbors for Behavioral Target Generalization in Sequential Recommendation. IEEE Trans. Netw. Sci. Eng. 9(3): 1658-1667 (2022) - 2021
- [j2]Han Liu, Xiaotong Zhang, Xianchao Zhang, Qimai Li, Xiao-Ming Wu:
RPC: Representative possible world based consistent clustering algorithm for uncertain data. Comput. Commun. 176: 128-137 (2021) - [j1]Xiaotong Zhang, Han Liu, Xiao-Ming Wu, Xianchao Zhang, Xinyue Liu:
Spectral embedding network for attributed graph clustering. Neural Networks 142: 388-396 (2021)
Conference and Workshop Papers
- 2024
- [c53]Cong Wang, Jinshan Pan, Wanyu Lin, Jiangxin Dong, Wei Wang, Xiao-Ming Wu:
SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency. AAAI 2024: 5327-5335 - [c52]Cong Wang, Jinshan Pan, Wei Wang, Gang Fu, Siyuan Liang, Mengzhu Wang, Xiao-Ming Wu, Jun Liu:
Correlation Matching Transformation Transformers for UHD Image Restoration. AAAI 2024: 5336-5344 - [c51]Yujie Feng, Xu Chu, Yongxin Xu, Guangyuan Shi, Bo Liu, Xiao-Ming Wu:
TaSL: Continual Dialog State Tracking via Task Skill Localization and Consolidation. ACL (1) 2024: 1266-1279 - [c50]Xiangyu Zhao, Bo Liu, Qijiong Liu, Guangyuan Shi, Xiao-Ming Wu:
EasyGen: Easing Multimodal Generation with BiDiffuser and LLMs. ACL (1) 2024: 1351-1370 - [c49]Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
Continual Dialogue State Tracking via Reason-of-Select Distillation. ACL (Findings) 2024: 7075-7087 - [c48]Bo Liu, Li-Ming Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu:
How Good Are LLMs at Out-of-Distribution Detection? LREC/COLING 2024: 8211-8222 - [c47]Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu:
LANID: LLM-assisted New Intent Discovery. LREC/COLING 2024: 10110-10116 - [c46]Xiangyu Zhao, Yuehan Zhang, Wenlong Zhang, Xiao-Ming Wu:
UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation. EMNLP 2024: 1490-1507 - [c45]Xiaoyu Dong, Yujie Feng, Zexin Lu, Guangyuan Shi, Xiao-Ming Wu:
Zero-shot Cross-domain Dialogue State Tracking via Context-aware Auto-prompting and Instruction-following Contrastive Decoding. EMNLP 2024: 8527-8540 - [c44]Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Xiaoyun Zhang, Yu Qiao, Xiao-Ming Wu, Chao Dong:
SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution. ICLR 2024 - [c43]Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong:
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. KDD 2024: 6566-6576 - [c42]Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu:
ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models. WSDM 2024: 452-461 - [c41]Qijiong Liu, Hengchang Hu, Jiahao Wu, Jieming Zhu, Min-Yen Kan, Xiao-Ming Wu:
Discrete Semantic Tokenization for Deep CTR Prediction. WWW (Companion Volume) 2024: 919-922 - [c40]Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu:
Benchmarking News Recommendation in the Era of Green AI. WWW (Companion Volume) 2024: 971-974 - [c39]Qijiong Liu, Jiaren Xiao, Lu Fan, Jieming Zhu, Xiao-Ming Wu:
Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization. WWW 2024: 3521-3532 - 2023
- [c38]Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Fenglong Ma, Xiao-Ming Wu, Hongyang Chen, Hong Yu, Xianchao Zhang:
Boosting Few-Shot Text Classification via Distribution Estimation. AAAI 2023: 13219-13227 - [c37]Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding:
Continual Graph Convolutional Network for Text Classification. AAAI 2023: 13754-13762 - [c36]Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training. ACL (Findings) 2023: 11105-11121 - [c35]Li Xu, Bo Liu, Ameer Hamza Khan, Lu Fan, Xiao-Ming Wu:
Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models. CHIL 2023: 117-132 - [c34]Yujie Feng, Zexin Lu, Bo Liu, Liming Zhan, Xiao-Ming Wu:
Towards LLM-driven Dialogue State Tracking. EMNLP 2023: 739-755 - [c33]Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu:
Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning. ICLR 2023 - [c32]Wenlong Zhang, Xiaohui Li, Guangyuan Shi, Xiangyu Chen, Yu Qiao, Xiaoyun Zhang, Xiao-Ming Wu, Chao Dong:
Real-World Image Super-Resolution as Multi-Task Learning. NeurIPS 2023 - [c31]Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu:
Neighborhood-based Hard Negative Mining for Sequential Recommendation. SIGIR 2023: 2042-2046 - [c30]Qijiong Liu, Jieming Zhu, Jiahao Wu, Tiandeng Wu, Zhenhua Dong, Xiao-Ming Wu:
FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation. WWW 2023: 3309-3318 - 2022
- [c29]Cong Wang, Jinshan Pan, Xiao-Ming Wu:
Online-Updated High-Order Collaborative Networks for Single Image Deraining. AAAI 2022: 2406-2413 - [c28]Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
New Intent Discovery with Pre-training and Contrastive Learning. ACL (1) 2022: 256-269 - [c27]Li-Ming Zhan, Haowen Liang, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam:
A Closer Look at Few-Shot Out-of-Distribution Intent Detection. COLING 2022: 451-460 - [c26]Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiaoming Wu:
Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation. COLING 2022: 2823-2833 - [c25]Wenlong Zhang, Guangyuan Shi, Yihao Liu, Chao Dong, Xiao-Ming Wu:
A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds. CVPR Workshops 2022: 526-535 - [c24]Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam:
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization. NAACL-HLT 2022: 532-542 - [c23]Lu Fan, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang:
Modeling User Behavior with Graph Convolution for Personalized Product Search. WWW 2022: 203-212 - 2021
- [c22]Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam:
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training. ACL/IJCNLP (1) 2021: 3521-3532 - [c21]Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam:
Effectiveness of Pre-training for Few-shot Intent Classification. EMNLP (Findings) 2021: 1114-1120 - [c20]Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu:
Slake: A Semantically-Labeled Knowledge-Enhanced Dataset For Medical Visual Question Answering. ISBI 2021: 1650-1654 - [c19]Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu:
Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs. KDD 2021: 953-963 - [c18]Sen Li, Fuyu Lv, Taiwei Jin, Guli Lin, Keping Yang, Xiaoyi Zeng, Xiao-Ming Wu, Qianli Ma:
Embedding-based Product Retrieval in Taobao Search. KDD 2021: 3181-3189 - [c17]Bo Liu, Li-Ming Zhan, Xiao-Ming Wu:
Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images. MICCAI (2) 2021: 210-220 - [c16]Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu:
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima. NeurIPS 2021: 6747-6761 - 2020
- [c15]Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung:
Variational Metric Scaling for Metric-Based Meta-Learning. AAAI 2020: 3478-3485 - [c14]Guangfeng Yan, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Xiao-Ming Wu, Albert Y. S. Lam:
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification. ACL 2020: 1050-1060 - [c13]Menghan Wang, Yujie Lin, Guli Lin, Keping Yang, Xiao-Ming Wu:
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems. KDD 2020: 2349-2358 - [c12]Li-Ming Zhan, Bo Liu, Lu Fan, Jiaxin Chen, Xiao-Ming Wu:
Medical Visual Question Answering via Conditional Reasoning. ACM Multimedia 2020: 2345-2354 - [c11]Jiaxin Chen, Xiao-Ming Wu, Yanke Li, Qimai Li, Li-Ming Zhan, Fu-Lai Chung:
A Closer Look at the Training Strategy for Modern Meta-Learning. NeurIPS 2020 - 2019
- [c10]Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, Zhichao Guan:
Label Efficient Semi-Supervised Learning via Graph Filtering. CVPR 2019: 9582-9591 - [c9]Han Liu, Xiaotong Zhang, Lu Fan, Xuandi Fu, Qimai Li, Xiao-Ming Wu, Albert Y. S. Lam:
Reconstructing Capsule Networks for Zero-shot Intent Classification. EMNLP/IJCNLP (1) 2019: 4798-4808 - [c8]Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu:
Attributed Graph Clustering via Adaptive Graph Convolution. IJCAI 2019: 4327-4333 - 2018
- [c7]Qimai Li, Zhichao Han, Xiao-Ming Wu:
Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning. AAAI 2018: 3538-3545 - 2015
- [c6]Xiao-Ming Wu, Zhenguo Li, Shih-Fu Chang:
New insights into Laplacian similarity search. CVPR 2015: 1949-1957 - 2014
- [c5]Go Irie, Zhenguo Li, Xiao-Ming Wu, Shih-Fu Chang:
Locally Linear Hashing for Extracting Non-linear Manifolds. CVPR 2014: 2123-2130 - 2013
- [c4]Xiao-Ming Wu, Zhenguo Li, Shih-Fu Chang:
Analyzing the Harmonic Structure in Graph-Based Learning. NIPS 2013: 3129-3137 - 2012
- [c3]Zhenguo Li, Xiao-Ming Wu, Shih-Fu Chang:
Segmentation using superpixels: A bipartite graph partitioning approach. CVPR 2012: 789-796 - [c2]Xiao-Ming Wu, Zhenguo Li, Anthony Man-Cho So, John Wright, Shih-Fu Chang:
Learning with Partially Absorbing Random Walks. NIPS 2012: 3086-3094 - 2009
- [c1]Xiao-Ming Wu, Anthony Man-Cho So, Zhenguo Li, Shuo-Yen Robert Li:
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite-Quadratic-Linear Programming. NIPS 2009: 1964-1972
Informal and Other Publications
- 2024
- [i55]Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu:
Benchmarking News Recommendation in the Era of Green AI. CoRR abs/2403.04736 (2024) - [i54]Qijiong Liu, Hengchang Hu, Jiahao Wu, Jieming Zhu, Min-Yen Kan, Xiao-Ming Wu:
Discrete Semantic Tokenization for Deep CTR Prediction. CoRR abs/2403.08206 (2024) - [i53]Nuo Chen, Jiqun Liu, Hanpei Fang, Yuankai Luo, Tetsuya Sakai, Xiao-Ming Wu:
Decoy Effect In Search Interaction: Understanding User Behavior and Measuring System Vulnerability. CoRR abs/2403.18462 (2024) - [i52]Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong:
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. CoRR abs/2404.00621 (2024) - [i51]Qijiong Liu, Xiaoyu Dong, Jiaren Xiao, Nuo Chen, Hengchang Hu, Jieming Zhu, Chenxu Zhu, Tetsuya Sakai, Xiao-Ming Wu:
Vector Quantization for Recommender Systems: A Review and Outlook. CoRR abs/2405.03110 (2024) - [i50]Yuankai Luo, Qijiong Liu, Lei Shi, Xiao-Ming Wu:
Structure-aware Semantic Node Identifiers for Learning on Graphs. CoRR abs/2405.16435 (2024) - [i49]Cong Wang, Jinshan Pan, Wei Wang, Gang Fu, Siyuan Liang, Mengzhu Wang, Xiao-Ming Wu, Jun Liu:
Correlation Matching Transformation Transformers for UHD Image Restoration. CoRR abs/2406.00629 (2024) - [i48]Yuankai Luo, Lei Shi, Xiao-Ming Wu:
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification. CoRR abs/2406.08993 (2024) - [i47]Yujie Feng, Xu Chu, Yongxin Xu, Zexin Lu, Bo Liu, Philip S. Yu, Xiao-Ming Wu:
TaSL: Task Skill Localization and Consolidation for Language Model Continual Learning. CoRR abs/2408.05200 (2024) - [i46]Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
Continual Dialogue State Tracking via Reason-of-Select Distillation. CoRR abs/2408.09846 (2024) - [i45]Yujie Feng, Xu Chu, Yongxin Xu, Guangyuan Shi, Bo Liu, Xiao-Ming Wu:
TaSL: Continual Dialog State Tracking via Task Skill Localization and Consolidation. CoRR abs/2408.09857 (2024) - [i44]Xiangyu Zhao, Yuehan Zhang, Wenlong Zhang, Xiao-Ming Wu:
UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation. CoRR abs/2408.11305 (2024) - [i43]Qijiong Liu, Jieming Zhu, Lu Fan, Zhou Zhao, Xiao-Ming Wu:
STORE: Streamlining Semantic Tokenization and Generative Recommendation with A Single LLM. CoRR abs/2409.07276 (2024) - [i42]Bo Liu, Liming Zhan, Yujie Feng, Zexin Lu, Chengqiang Xie, Lei Xue, Albert Y. S. Lam, Xiao-Ming Wu:
Diversity-grounded Channel Prototypical Learning for Out-of-Distribution Intent Detection. CoRR abs/2409.11114 (2024) - [i41]Nuo Chen, Jiqun Liu, Xiaoyu Dong, Qijiong Liu, Tetsuya Sakai, Xiao-Ming Wu:
AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment. CoRR abs/2409.16022 (2024) - 2023
- [i40]Yulin Zhu, Xing Ai, Qimai Li, Xiao-Ming Wu, Kai Zhou:
Simple yet Effective Gradient-Free Graph Convolutional Networks. CoRR abs/2302.00371 (2023) - [i39]Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu:
Recon: Reducing Conflicting Gradients from the Root for Multi-Task Learning. CoRR abs/2302.11289 (2023) - [i38]Cong Wang, Jinshan Pan, Wanyu Lin, Jiangxin Dong, Xiao-Ming Wu:
SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency. CoRR abs/2303.07033 (2023) - [i37]Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Fenglong Ma, Xiao-Ming Wu, Hongyang Chen, Hong Yu, Xianchao Zhang:
Boosting Few-Shot Text Classification via Distribution Estimation. CoRR abs/2303.16764 (2023) - [i36]Qijiong Liu, Jieming Zhu, Jiahao Wu, Tiandeng Wu, Zhenhua Dong, Xiao-Ming Wu:
FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation. CoRR abs/2304.00545 (2023) - [i35]Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding:
Continual Graph Convolutional Network for Text Classification. CoRR abs/2304.04152 (2023) - [i34]Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu:
A First Look at LLM-Powered Generative News Recommendation. CoRR abs/2305.06566 (2023) - [i33]Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training. CoRR abs/2306.05278 (2023) - [i32]Li Xu, Bo Liu, Ameer Hamza Khan, Lu Fan, Xiao-Ming Wu:
Multi-modal Pre-training for Medical Vision-language Understanding and Generation: An Empirical Study with A New Benchmark. CoRR abs/2306.06494 (2023) - [i31]Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu:
Neighborhood-based Hard Negative Mining for Sequential Recommendation. CoRR abs/2306.10047 (2023) - [i30]Bo Liu, Liming Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu:
How Good Are Large Language Models at Out-of-Distribution Detection? CoRR abs/2308.10261 (2023) - [i29]Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu:
Only Encode Once: Making Content-based News Recommender Greener. CoRR abs/2308.14155 (2023) - [i28]Qijiong Liu, Jiaren Xiao, Lu Fan, Jieming Zhu, Xiao-Ming Wu:
Co-evolving Vector Quantization for ID-based Recommendation. CoRR abs/2308.16761 (2023) - [i27]Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Yu Qiao, Xiao-Ming Wu, Chao Dong:
SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution. CoRR abs/2309.03020 (2023) - [i26]Xiangyu Zhao, Bo Liu, Qijiong Liu, Guangyuan Shi, Xiao-Ming Wu:
Making Multimodal Generation Easier: When Diffusion Models Meet LLMs. CoRR abs/2310.08949 (2023) - [i25]Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang:
Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation. CoRR abs/2310.09874 (2023) - [i24]Yujie Feng, Zexin Lu, Bo Liu, Liming Zhan, Xiao-Ming Wu:
Towards LLM-driven Dialogue State Tracking. CoRR abs/2310.14970 (2023) - [i23]Nuo Chen, Jiqun Liu, Tetsuya Sakai, Xiao-Ming Wu:
Decoy Effect in Search Interaction: A Pilot Study. CoRR abs/2311.02362 (2023) - 2022
- [i22]Fan Lu, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang:
Modeling User Behavior with Graph Convolution for Personalized Product Search. CoRR abs/2202.06081 (2022) - [i21]Cong Wang, Jinshan Pan, Xiao-Ming Wu:
Online-updated High-order Collaborative Networks for Single Image Deraining. CoRR abs/2202.06568 (2022) - [i20]Wenlong Zhang, Guangyuan Shi, Yihao Liu, Chao Dong, Xiao-Ming Wu:
A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds. CoRR abs/2205.04910 (2022) - [i19]Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam:
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization. CoRR abs/2205.07208 (2022) - [i18]Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam:
New Intent Discovery with Pre-training and Contrastive Learning. CoRR abs/2205.12914 (2022) - [i17]Cong Wang, Jinshan Pan, Xiao-Ming Wu:
Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement. CoRR abs/2207.07828 (2022) - 2021
- [i16]Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu:
SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering. CoRR abs/2102.09542 (2021) - [i15]Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam:
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training. CoRR abs/2106.08616 (2021) - [i14]Sen Li, Fuyu Lv, Taiwei Jin, Guli Lin, Keping Yang, Xiaoyi Zeng, Xiao-Ming Wu, Qianli Ma:
Embedding-based Product Retrieval in Taobao Search. CoRR abs/2106.09297 (2021) - [i13]Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung:
Adaptation-Agnostic Meta-Training. CoRR abs/2108.10557 (2021) - [i12]Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam:
Effectiveness of Pre-training for Few-shot Intent Classification. CoRR abs/2109.05782 (2021) - [i11]Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu:
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima. CoRR abs/2111.01549 (2021) - 2020
- [i10]Zhen Peng, Yixiang Dong, Minnan Luo, Xiao-Ming Wu, Qinghua Zheng:
Self-Supervised Graph Representation Learning via Global Context Prediction. CoRR abs/2003.01604 (2020) - [i9]Menghan Wang, Yujie Lin, Guli Lin, Keping Yang, Xiao-Ming Wu:
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems. CoRR abs/2005.10110 (2020) - 2019
- [i8]Qimai Li, Xiao-Ming Wu, Zhichao Guan:
Generalized Label Propagation Methods for Semi-Supervised Learning. CoRR abs/1901.09993 (2019) - [i7]Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu:
Attributed Graph Clustering via Adaptive Graph Convolution. CoRR abs/1906.01210 (2019) - [i6]Quanyu Dai, Xiao Shen, Xiao-Ming Wu, Dan Wang:
Network Transfer Learning via Adversarial Domain Adaptation with Graph Convolution. CoRR abs/1909.01541 (2019) - [i5]Qimai Li, Xiaotong Zhang, Han Liu, Xiao-Ming Wu:
Attributed Graph Learning with 2-D Graph Convolution. CoRR abs/1909.12038 (2019) - [i4]Han Liu, Xianchao Zhang, Xiaotong Zhang, Qimai Li, Xiao-Ming Wu:
Clustering Uncertain Data via Representative Possible Worlds with Consistency Learning. CoRR abs/1909.12514 (2019) - [i3]Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung:
Variational Metric Scaling for Metric-Based Meta-Learning. CoRR abs/1912.11809 (2019) - 2018
- [i2]Qimai Li, Zhichao Han, Xiao-Ming Wu:
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning. CoRR abs/1801.07606 (2018) - [i1]Yong Wang, Xiao-Ming Wu, Qimai Li, Jiatao Gu, Wangmeng Xiang, Lei Zhang, Victor O. K. Li:
Large Margin Few-Shot Learning. CoRR abs/1807.02872 (2018)
Coauthor Index
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of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-15 19:33 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
