Xiao-Ming Wu

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 85

Top Topics

Convolutional Network

Question Answering

Supervised Learning

Top Venues

Publications

Yuankai Luo, Lei Shi, Xiao-Ming Wu
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification. CoRR (2024)
Qijiong Liu, Hengchang Hu, Jiahao Wu, Jieming Zhu, Min-Yen Kan, Xiao-Ming Wu
Discrete Semantic Tokenization for Deep CTR Prediction. CoRR (2024)
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 (2024)
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 (2024)
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)
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 (2024)
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)
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)
Xiangyu Zhao, Bo Liu, Qijiong Liu, Guangyuan Shi, Xiao-Ming Wu
EasyGen: Easing Multimodal Generation with BiDiffuser and LLMs. ACL (1) (2024)
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)
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)
Yuankai Luo, Qijiong Liu, Lei Shi, Xiao-Ming Wu
Structure-aware Semantic Node Identifiers for Learning on Graphs. CoRR (2024)
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)
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)
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)
Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu
Benchmarking News Recommendation in the Era of Green AI. WWW (Companion Volume) (2024)
Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu
LANID: LLM-assisted New Intent Discovery. LREC/COLING (2024)
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 (2024)
Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu
Benchmarking News Recommendation in the Era of Green AI. CoRR (2024)
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)
Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu
Neighborhood-based Hard Negative Mining for Sequential Recommendation. CoRR (2023)
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)
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 (2023)
Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu
Recon: Reducing Conflicting Gradients from the Root for Multi-Task Learning. CoRR (2023)
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 (2023)
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 (2023)
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) (2023)
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)
Yulin Zhu, Xing Ai, Qimai Li, Xiao-Ming Wu, Kai Zhou
Simple yet Effective Gradient-Free Graph Convolutional Networks. CoRR (2023)
Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding
Continual Graph Convolutional Network for Text Classification. AAAI (2023)
Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu
A First Look at LLM-Powered Generative News Recommendation. CoRR (2023)
Qijiong Liu, Jieming Zhu, Jiahao Wu, Tiandeng Wu, Zhenhua Dong, Xiao-Ming Wu
FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation. CoRR (2023)
Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu
Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning. ICLR (2023)
Xiangyu Zhao, Bo Liu, Qijiong Liu, Guangyuan Shi, Xiao-Ming Wu
Making Multimodal Generation Easier: When Diffusion Models Meet LLMs. CoRR (2023)
Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu
Neighborhood-based Hard Negative Mining for Sequential Recommendation. SIGIR (2023)
Nuo Chen, Jiqun Liu, Tetsuya Sakai, Xiao-Ming Wu
Decoy Effect in Search Interaction: A Pilot Study. CoRR (2023)
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)
Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu
Only Encode Once: Making Content-based News Recommender Greener. CoRR (2023)
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)
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 (2023)
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) (2023)
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 (2022)
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)
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 (2022)
Zhen Peng, Yixiang Dong, Minnan Luo, Xiao-Ming Wu, Qinghua Zheng
A new self-supervised task on graphs: Geodesic distance prediction. Inf. Sci. 607 (2022)
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)
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 (2022)
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)
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 (2022)
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)
Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
New Intent Discovery with Pre-training and Contrastive Learning. CoRR (2022)
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) (2022)
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 (2021)
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)
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)
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 (2021)
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 (2021)
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)
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 (2021)
Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung
Adaptation-Agnostic Meta-Training. CoRR (2021)
Xiaotong Zhang, Han Liu, Xiao-Ming Wu, Xianchao Zhang, Xinyue Liu
Spectral embedding network for attributed graph clustering. Neural Networks 142 (2021)
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)
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 (2021)
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)
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 (2021)
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)
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)
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)
Li-Ming Zhan, Bo Liu, Lu Fan, Jiaxin Chen, Xiao-Ming Wu
Medical Visual Question Answering via Conditional Reasoning. ACM Multimedia (2020)
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)
Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung
Variational Metric Scaling for Metric-Based Meta-Learning. AAAI (2020)
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 (2020)
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)
Quanyu Dai, Xiao Shen, Xiao-Ming Wu, Dan Wang
Network Transfer Learning via Adversarial Domain Adaptation with Graph Convolution. CoRR (2019)
Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung
Variational Metric Scaling for Metric-Based Meta-Learning. CoRR (2019)
Qimai Li, Xiao-Ming Wu, Zhichao Guan
Generalized Label Propagation Methods for Semi-Supervised Learning. CoRR (2019)
Han Liu, Xianchao Zhang, Xiaotong Zhang, Qimai Li, Xiao-Ming Wu
Clustering Uncertain Data via Representative Possible Worlds with Consistency Learning. CoRR (2019)
Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu
Attributed Graph Clustering via Adaptive Graph Convolution. IJCAI (2019)
Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, Zhichao Guan
Label Efficient Semi-Supervised Learning via Graph Filtering. CVPR (2019)
Qimai Li, Xiaotong Zhang, Han Liu, Xiao-Ming Wu
Attributed Graph Learning with 2-D Graph Convolution. CoRR (2019)
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)
Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu
Attributed Graph Clustering via Adaptive Graph Convolution. CoRR (2019)
Qimai Li, Zhichao Han, Xiao-Ming Wu
Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning. AAAI (2018)
Qimai Li, Zhichao Han, Xiao-Ming Wu
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning. CoRR (2018)
Yong Wang, Xiao-Ming Wu, Qimai Li, Jiatao Gu, Wangmeng Xiang, Lei Zhang, Victor O. K. Li
Large Margin Few-Shot Learning. CoRR (2018)
Xiao-Ming Wu, Zhenguo Li, Shih-Fu Chang
New insights into Laplacian similarity search. CVPR (2015)
Go Irie, Zhenguo Li, Xiao-Ming Wu, Shih-Fu Chang
Locally Linear Hashing for Extracting Non-linear Manifolds. CVPR (2014)
Zhenguo Li, Xiao-Ming Wu, Shih-Fu Chang
Segmentation using superpixels: A bipartite graph partitioning approach. CVPR (2012)