Xiao-Ming Wu

147 papers A* 38A 3B 1Journal 80Unranked 25
YearRankTypeTitle / Venue / Authors
2026 A conf
Accelerating Generative Recommendation via Simple Categorical User Sequence Compression.
WSDM
Qijiong Liu, Lu Fan, Zhongzhou Liu, Xiaoyu Dong, Yuankai Luo, Guoyuan An, Nuo Chen, Wei Guo, Yong Liu, Xiao-Ming Wu
2026 J jnl
Accelerating Generative Recommendation via Simple Categorical User Sequence Compression.
CoRR
Qijiong Liu, Lu Fan, Zhongzhou Liu, Xiaoyu Dong, Yuankai Luo, Guoyuan An, Nuo Chen, Wei Guo, Yong Liu, Xiao-Ming Wu
2026 J jnl
Judging with Personality and Confidence: A Study on Personality-Conditioned LLM Relevance Assessment.
CoRR
Nuo Chen, Hanpei Fang, Piaohong Wang, Jiqun Liu, Tetsuya Sakai, Xiao-Ming Wu
2026 A conf
Mitigating the Threshold Priming Effect in Large Language Model-Based Relevance Judgments via Personality Simulation.
WSDM
Nuo Chen, Hanpei Fang, Jiqun Liu, Wilson Wei, Tetsuya Sakai, Xiao-Ming Wu
2025 J jnl
Benchmarking LLMs in Recommendation Tasks: A Comparative Evaluation with Conventional Recommenders.
CoRR
Qijiong Liu, Jieming Zhu, Lu Fan, Kun Wang, Hengchang Hu, Wei Guo, Yong Liu, Xiao-Ming Wu
2025 A* conf
Beyond Random Masking: When Dropout meets Graph Convolutional Networks.
ICLR
Yuankai Luo, Xiao-Ming Wu, Hao Zhu
2025 A* conf
Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet Excellence.
ICML
Yuankai Luo, Lei Shi, Xiao-Ming Wu
2025 J jnl
DEAL: Disentangling Transformer Head Activations for LLM Steering.
CoRR
Li-Ming Zhan, Bo Liu, Zexin Lu, Chengqiang Xie, Jiannong Cao, Xiao-Ming Wu
2025 J jnl
Decoy Effect in Search Interaction: Understanding User Behavior and Measuring System Vulnerability.
ACM Trans. Inf. Syst.
Nuo Chen, Jiqun Liu, Hanpei Fang, Yuankai Luo, Tetsuya Sakai, Xiao-Ming Wu
2025 J jnl
Evaluating Conversational Recommender Systems with Large Language Models: A User-Centric Evaluation Framework.
CoRR
Nuo Chen, Quanyu Dai, Xiaoyu Dong, Xiao-Ming Wu, Zhenhua Dong
2025 A* conf
GEMeX-RMCoT: An Enhanced Med-VQA Dataset for Region-Aware Multimodal Chain-of-Thought Reasoning.
ACM Multimedia
Bo Liu, Xiangyu Zhao, Along He, Yidi Chen, Huazhu Fu, Xiao-Ming Wu
2025 A* conf
GeoEdit: Geometric Knowledge Editing for Large Language Models.
EMNLP
Yujie Feng, Li-Ming Zhan, Zexin Lu, Yongxin Xu, Xu Chu, Yasha Wang, Jiannong Cao, Philip S. Yu, Xiao-Ming Wu
2025 J jnl
GeoEdit: Geometric Knowledge Editing for Large Language Models.
CoRR
Yujie Feng, Liming Zhan, Zexin Lu, Yongxin Xu, Xu Chu, Yasha Wang, Jiannong Cao, Philip S. Yu, Xiao-Ming Wu
2025 J jnl
LANID: LLM-assisted New Intent Discovery.
CoRR
Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu
2025 — conf
Legommenders: A Comprehensive Content-Based Recommendation Library with LLM Support.
WWW (Companion Volume)
Qijiong Liu, Lu Fan, Xiao-Ming Wu
2025 — conf
Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation.
WWW (Companion Volume)
Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang
2025 A* conf
MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising.
WWW
Quanyu Dai, Jiaren Xiao, Zhaocheng Du, Jieming Zhu, Chengxiao Luo, Xiao-Ming Wu, Zhenhua Dong
2025 J jnl
MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising.
CoRR
Quanyu Dai, Jiaren Xiao, Zhaocheng Du, Jieming Zhu, Chengxiao Luo, Xiao-Ming Wu, Zhenhua Dong
2025 J jnl
Mitigating the Threshold Priming Effect in Large Language Model-Based Relevance Judgments via Personality Infusing.
CoRR
Nuo Chen, Hanpei Fang, Jiqun Liu, Wilson Wei, Tetsuya Sakai, Xiao-Ming Wu
2025 A* conf
Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning.
ICLR
Yuankai Luo, Hongkang Li, Qijiong Liu, Lei Shi, Xiao-Ming Wu
2025 — conf
Recurrent Knowledge Identification and Fusion for Language Model Continual Learning.
ACL (1)
Yujie Feng, Xujia Wang, Zexin Lu, Shenghong Fu, Guangyuan Shi, Yongxin Xu, Yasha Wang, Philip S. Yu, Xu Chu, Xiao-Ming Wu
2025 J jnl
Recurrent Knowledge Identification and Fusion for Language Model Continual Learning.
CoRR
Yujie Feng, Xujia Wang, Zexin Lu, Shenghong Fu, Guangyuan Shi, Yongxin Xu, Yasha Wang, Philip S. Yu, Xu Chu, Xiao-Ming Wu
2025 J jnl
SolBench: A Dataset and Benchmark for Evaluating Functional Correctness in Solidity Code Completion and Repair.
CoRR
Zaoyu Chen, Haoran Qin, Nuo Chen, Xiangyu Zhao, Lei Xue, Xiapu Luo, Xiao-Ming Wu
2025 J jnl
Unlocking the Potential of Classic GNNs for Graph-level Tasks: Simple Architectures Meet Excellence.
CoRR
Yuankai Luo, Lei Shi, Xiao-Ming Wu
2024 — conf
AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment.
SIGIR-AP
Nuo Chen, Jiqun Liu, Xiaoyu Dong, Qijiong Liu, Tetsuya Sakai, Xiao-Ming Wu
2024 J jnl
AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment.
CoRR
Nuo Chen, Jiqun Liu, Xiaoyu Dong, Qijiong Liu, Tetsuya Sakai, Xiao-Ming Wu
2024 — conf
Benchmarking News Recommendation in the Era of Green AI.
WWW (Companion Volume)
Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu
2024 J jnl
Benchmarking News Recommendation in the Era of Green AI.
CoRR
Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu
2024 A* conf
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification.
NeurIPS
Yuankai Luo, Lei Shi, Xiao-Ming Wu
2024 J jnl
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification.
CoRR
Yuankai Luo, Lei Shi, Xiao-Ming Wu
2024 — conf
Continual Dialogue State Tracking via Reason-of-Select Distillation.
ACL (Findings)
Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2024 J jnl
Continual Dialogue State Tracking via Reason-of-Select Distillation.
CoRR
Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2024 A* conf
Correlation Matching Transformation Transformers for UHD Image Restoration.
AAAI
Cong Wang, Jinshan Pan, Wei Wang, Gang Fu, Siyuan Liang, Mengzhu Wang, Xiao-Ming Wu, Jun Liu
2024 J jnl
Correlation Matching Transformation Transformers for UHD Image Restoration.
CoRR
Cong Wang, Jinshan Pan, Wei Wang, Gang Fu, Siyuan Liang, Mengzhu Wang, Xiao-Ming Wu, Jun Liu
2024 J jnl
Decoy Effect In Search Interaction: Understanding User Behavior and Measuring System Vulnerability.
CoRR
Nuo Chen, Jiqun Liu, Hanpei Fang, Yuankai Luo, Tetsuya Sakai, Xiao-Ming Wu
2024 — conf
Discrete Semantic Tokenization for Deep CTR Prediction.
WWW (Companion Volume)
Qijiong Liu, Hengchang Hu, Jiahao Wu, Jieming Zhu, Min-Yen Kan, Xiao-Ming Wu
2024 J jnl
Discrete Semantic Tokenization for Deep CTR Prediction.
CoRR
Qijiong Liu, Hengchang Hu, Jiahao Wu, Jieming Zhu, Min-Yen Kan, Xiao-Ming Wu
2024 J jnl
Diversity-grounded Channel Prototypical Learning for Out-of-Distribution Intent Detection.
CoRR
Bo Liu, Liming Zhan, Yujie Feng, Zexin Lu, Chengqiang Xie, Lei Xue, Albert Y. S. Lam, Xiao-Ming Wu
2024 — conf
EasyGen: Easing Multimodal Generation with BiDiffuser and LLMs.
ACL (1)
Xiangyu Zhao, Bo Liu, Qijiong Liu, Guangyuan Shi, Xiao-Ming Wu
2024 A* conf
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding.
NeurIPS
Yuankai Luo, Hongkang Li, Lei Shi, Xiao-Ming Wu
2024 J jnl
GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis.
CoRR
Bo Liu, Ke Zou, Liming Zhan, Zexin Lu, Xiaoyu Dong, Yidi Chen, Chengqiang Xie, Jiannong Cao, Xiao-Ming Wu, Huazhu Fu
2024 — conf
How Good Are LLMs at Out-of-Distribution Detection?
LREC/COLING
Bo Liu, Li-Ming Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu
2024 — conf
LANID: LLM-assisted New Intent Discovery.
LREC/COLING
Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu
2024 A* conf
Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization.
WWW
Qijiong Liu, Jiaren Xiao, Lu Fan, Jieming Zhu, Xiao-Ming Wu
2024 J jnl
Legommenders: A Comprehensive Content-Based Recommendation Library with LLM Support.
CoRR
Qijiong Liu, Lu Fan, Xiao-Ming Wu
2024 A* conf
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey.
KDD
Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong
2024 J jnl
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey.
CoRR
Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong
2024 A conf
ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models.
WSDM
Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu
2024 A* conf
SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution.
ICLR
Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Xiaoyun Zhang, Yu Qiao, Xiao-Ming Wu, Chao Dong
2024 J jnl
STORE: Streamlining Semantic Tokenization and Generative Recommendation with A Single LLM.
CoRR
Qijiong Liu, Jieming Zhu, Lu Fan, Zhou Zhao, Xiao-Ming Wu
2024 A* conf
SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency.
AAAI
Cong Wang, Jinshan Pan, Wanyu Lin, Jiangxin Dong, Wei Wang, Xiao-Ming Wu
2024 J jnl
Structure-aware Semantic Node Identifiers for Learning on Graphs.
CoRR
Yuankai Luo, Qijiong Liu, Lei Shi, Xiao-Ming Wu
2024 — conf
TaSL: Continual Dialog State Tracking via Task Skill Localization and Consolidation.
ACL (1)
Yujie Feng, Xu Chu, Yongxin Xu, Guangyuan Shi, Bo Liu, Xiao-Ming Wu
2024 J jnl
TaSL: Continual Dialog State Tracking via Task Skill Localization and Consolidation.
CoRR
Yujie Feng, Xu Chu, Yongxin Xu, Guangyuan Shi, Bo Liu, Xiao-Ming Wu
2024 J jnl
TaSL: Task Skill Localization and Consolidation for Language Model Continual Learning.
CoRR
Yujie Feng, Xu Chu, Yongxin Xu, Zexin Lu, Bo Liu, Philip S. Yu, Xiao-Ming Wu
2024 J jnl
Understanding Layer Significance in LLM Alignment.
CoRR
Guangyuan Shi, Zexin Lu, Xiaoyu Dong, Wenlong Zhang, Xuanyu Zhang, Yujie Feng, Xiao-Ming Wu
2024 A* conf
UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation.
EMNLP
Xiangyu Zhao, Yuehan Zhang, Wenlong Zhang, Xiao-Ming Wu
2024 J jnl
UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation.
CoRR
Xiangyu Zhao, Yuehan Zhang, Wenlong Zhang, Xiao-Ming Wu
2024 J jnl
Vector Quantization for Recommender Systems: A Review and Outlook.
CoRR
Qijiong Liu, Xiaoyu Dong, Jiaren Xiao, Nuo Chen, Hengchang Hu, Jieming Zhu, Chenxu Zhu, Tetsuya Sakai, Xiao-Ming Wu
2024 A* conf
Zero-shot Cross-domain Dialogue State Tracking via Context-aware Auto-prompting and Instruction-following Contrastive Decoding.
EMNLP
Xiaoyu Dong, Yujie Feng, Zexin Lu, Guangyuan Shi, Xiao-Ming Wu
2023 J jnl
A First Look at LLM-Powered Generative News Recommendation.
CoRR
Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu
2023 J jnl
Adaptive Graph Convolution Methods for Attributed Graph Clustering.
IEEE Trans. Knowl. Data Eng.
Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu, Xianchao Zhang
2023 A* conf
Boosting Few-Shot Text Classification via Distribution Estimation.
AAAI
Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Fenglong Ma, Xiao-Ming Wu, Hongyang Chen, Hong Yu, Xianchao Zhang
2023 J jnl
Boosting Few-Shot Text Classification via Distribution Estimation.
CoRR
Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Fenglong Ma, Xiao-Ming Wu, Hongyang Chen, Hong Yu, Xianchao Zhang
2023 J jnl
Co-evolving Vector Quantization for ID-based Recommendation.
CoRR
Qijiong Liu, Jiaren Xiao, Lu Fan, Jieming Zhu, Xiao-Ming Wu
2023 A* conf
Continual Graph Convolutional Network for Text Classification.
AAAI
Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding
2023 J jnl
Continual Graph Convolutional Network for Text Classification.
CoRR
Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding
2023 — conf
Decoy Effect in Search Interaction: A Pilot Study.
EVIA
Nuo Chen, Jiqun Liu, Tetsuya Sakai, Xiao-Ming Wu
2023 J jnl
Decoy Effect in Search Interaction: A Pilot Study.
CoRR
Nuo Chen, Jiqun Liu, Tetsuya Sakai, Xiao-Ming Wu
2023 A* conf
FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation.
WWW
Qijiong Liu, Jieming Zhu, Jiahao Wu, Tiandeng Wu, Zhenhua Dong, Xiao-Ming Wu
2023 J jnl
FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation.
CoRR
Qijiong Liu, Jieming Zhu, Jiahao Wu, Tiandeng Wu, Zhenhua Dong, Xiao-Ming Wu
2023 J jnl
Graph Transfer Learning via Adversarial Domain Adaptation With Graph Convolution.
IEEE Trans. Knowl. Data Eng.
Quanyu Dai, Xiao-Ming Wu, Jiaren Xiao, Xiao Shen, Dan Wang
2023 J jnl
How Good Are Large Language Models at Out-of-Distribution Detection?
CoRR
Bo Liu, Liming Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu
2023 J jnl
Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation.
CoRR
Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang
2023 J jnl
Making Multimodal Generation Easier: When Diffusion Models Meet LLMs.
CoRR
Xiangyu Zhao, Bo Liu, Qijiong Liu, Guangyuan Shi, Xiao-Ming Wu
2023 J jnl
Medical Visual Question Answering via Conditional Reasoning and Contrastive Learning.
IEEE Trans. Medical Imaging
Bo Liu, Li-Ming Zhan, Li Xu, Xiao-Ming Wu
2023 — conf
Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models.
CHIL
Li Xu, Bo Liu, Ameer Hamza Khan, Lu Fan, Xiao-Ming Wu
2023 J jnl
Multi-modal Pre-training for Medical Vision-language Understanding and Generation: An Empirical Study with A New Benchmark.
CoRR
Li Xu, Bo Liu, Ameer Hamza Khan, Lu Fan, Xiao-Ming Wu
2023 A* conf
Neighborhood-based Hard Negative Mining for Sequential Recommendation.
SIGIR
Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu
2023 J jnl
Neighborhood-based Hard Negative Mining for Sequential Recommendation.
CoRR
Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu
2023 J jnl
Only Encode Once: Making Content-based News Recommender Greener.
CoRR
Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu
2023 A* conf
Real-World Image Super-Resolution as Multi-Task Learning.
NeurIPS
Wenlong Zhang, Xiaohui Li, Guangyuan Shi, Xiangyu Chen, Yu Qiao, Xiaoyun Zhang, Xiao-Ming Wu, Chao Dong
2023 A* conf
Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning.
ICLR
Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu
2023 J jnl
Recon: Reducing Conflicting Gradients from the Root for Multi-Task Learning.
CoRR
Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu
2023 — conf
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training.
ACL (Findings)
Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2023 J jnl
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training.
CoRR
Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2023 J jnl
SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution.
CoRR
Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Yu Qiao, Xiao-Ming Wu, Chao Dong
2023 J jnl
SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency.
CoRR
Cong Wang, Jinshan Pan, Wanyu Lin, Jiangxin Dong, Xiao-Ming Wu
2023 J jnl
Simple yet Effective Gradient-Free Graph Convolutional Networks.
CoRR
Yulin Zhu, Xing Ai, Qimai Li, Xiao-Ming Wu, Kai Zhou
2023 A* conf
Towards LLM-driven Dialogue State Tracking.
EMNLP
Yujie Feng, Zexin Lu, Bo Liu, Liming Zhan, Xiao-Ming Wu
2023 J jnl
Towards LLM-driven Dialogue State Tracking.
CoRR
Yujie Feng, Zexin Lu, Bo Liu, Liming Zhan, Xiao-Ming Wu
2022 — conf
A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds.
CVPR Workshops
Wenlong Zhang, Guangyuan Shi, Yihao Liu, Chao Dong, Xiao-Ming Wu
2022 J jnl
A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds.
CoRR
Wenlong Zhang, Guangyuan Shi, Yihao Liu, Chao Dong, Xiao-Ming Wu
2022 B conf
A Closer Look at Few-Shot Out-of-Distribution Intent Detection.
COLING
Li-Ming Zhan, Haowen Liang, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam
2022 J jnl
A new self-supervised task on graphs: Geodesic distance prediction.
Inf. Sci.
Zhen Peng, Yixiang Dong, Minnan Luo, Xiao-Ming Wu, Qinghua Zheng
2022 — conf
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization.
NAACL-HLT
Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam
2022 J jnl
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization.
CoRR
Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam
2022 J jnl
Meta-Path Based Neighbors for Behavioral Target Generalization in Sequential Recommendation.
IEEE Trans. Netw. Sci. Eng.
Junyang Chen, Zhiguo Gong, Yuanman Li, Huanjian Zhang, Hongyong Yu, Junzhang Zhu, Ge Fan, Xiao-Ming Wu, Kaishun Wu
2022 A* conf
Modeling User Behavior with Graph Convolution for Personalized Product Search.
WWW
Lu Fan, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang
2022 J jnl
Modeling User Behavior with Graph Convolution for Personalized Product Search.
CoRR
Fan Lu, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang
2022 — conf
New Intent Discovery with Pre-training and Contrastive Learning.
ACL (1)
Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2022 J jnl
New Intent Discovery with Pre-training and Contrastive Learning.
CoRR
Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam
2022 A* conf
Online-Updated High-Order Collaborative Networks for Single Image Deraining.
AAAI
Cong Wang, Jinshan Pan, Xiao-Ming Wu
2022 J jnl
Online-updated High-order Collaborative Networks for Single Image Deraining.
CoRR
Cong Wang, Jinshan Pan, Xiao-Ming Wu
2022 J jnl
Personalized knowledge-aware recommendation with collaborative and attentive graph convolutional networks.
Pattern Recognit.
Quanyu Dai, Xiao-Ming Wu, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Dan Wang, Guli Lin, Keping Yang
2022 J jnl
Single image rain removal using recurrent scale-guide networks.
Neurocomputing
Cong Wang, Honghe Zhu, Wanshu Fan, Xiao-Ming Wu, Junyang Chen
2022 J jnl
Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement.
CoRR
Cong Wang, Jinshan Pan, Xiao-Ming Wu
2021 J jnl
Adaptation-Agnostic Meta-Training.
CoRR
Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung
2021 — conf
Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images.
MICCAI (2)
Bo Liu, Li-Ming Zhan, Xiao-Ming Wu
2021 A* conf
Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs.
KDD
Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu
2021 — conf
Effectiveness of Pre-training for Few-shot Intent Classification.
EMNLP (Findings)
Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam
2021 J jnl
Effectiveness of Pre-training for Few-shot Intent Classification.
CoRR
Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam
2021 A* conf
Embedding-based Product Retrieval in Taobao Search.
KDD
Sen Li, Fuyu Lv, Taiwei Jin, Guli Lin, Keping Yang, Xiaoyi Zeng, Xiao-Ming Wu, Qianli Ma
2021 J jnl
Embedding-based Product Retrieval in Taobao Search.
CoRR
Sen Li, Fuyu Lv, Taiwei Jin, Guli Lin, Keping Yang, Xiaoyi Zeng, Xiao-Ming Wu, Qianli Ma
2021 — conf
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training.
ACL/IJCNLP (1)
Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam
2021 J jnl
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training.
CoRR
Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam
2021 A* conf
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima.
NeurIPS
Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu
2021 J jnl
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima.
CoRR
Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu
2021 J jnl
RPC: Representative possible world based consistent clustering algorithm for uncertain data.
Comput. Commun.
Han Liu, Xiaotong Zhang, Xianchao Zhang, Qimai Li, Xiao-Ming Wu
2021 J jnl
SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering.
CoRR
Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu
2021 — conf
Slake: A Semantically-Labeled Knowledge-Enhanced Dataset For Medical Visual Question Answering.
ISBI
Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu
2021 J jnl
Spectral embedding network for attributed graph clustering.
Neural Networks
Xiaotong Zhang, Han Liu, Xiao-Ming Wu, Xianchao Zhang, Xinyue Liu
2020 A* conf
A Closer Look at the Training Strategy for Modern Meta-Learning.
NeurIPS
Jiaxin Chen, Xiao-Ming Wu, Yanke Li, Qimai Li, Li-Ming Zhan, Fu-Lai Chung
2020 A* conf
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems.
KDD
Menghan Wang, Yujie Lin, Guli Lin, Keping Yang, Xiao-Ming Wu
2020 J jnl
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems.
CoRR
Menghan Wang, Yujie Lin, Guli Lin, Keping Yang, Xiao-Ming Wu
2020 A* conf
Medical Visual Question Answering via Conditional Reasoning.
ACM Multimedia
Li-Ming Zhan, Bo Liu, Lu Fan, Jiaxin Chen, Xiao-Ming Wu
2020 J jnl
Self-Supervised Graph Representation Learning via Global Context Prediction.
CoRR
Zhen Peng, Yixiang Dong, Minnan Luo, Xiao-Ming Wu, Qinghua Zheng
2020 A* conf
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification.
ACL
Guangfeng Yan, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Xiao-Ming Wu, Albert Y. S. Lam
2020 A* conf
Variational Metric Scaling for Metric-Based Meta-Learning.
AAAI
Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung
2019 A* conf
Attributed Graph Clustering via Adaptive Graph Convolution.
IJCAI
Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu
2019 J jnl
Attributed Graph Clustering via Adaptive Graph Convolution.
CoRR
Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu
2019 J jnl
Attributed Graph Learning with 2-D Graph Convolution.
CoRR
Qimai Li, Xiaotong Zhang, Han Liu, Xiao-Ming Wu
2019 J jnl
Clustering Uncertain Data via Representative Possible Worlds with Consistency Learning.
CoRR
Han Liu, Xianchao Zhang, Xiaotong Zhang, Qimai Li, Xiao-Ming Wu
2019 J jnl
Generalized Label Propagation Methods for Semi-Supervised Learning.
CoRR
Qimai Li, Xiao-Ming Wu, Zhichao Guan
2019 A* conf
Label Efficient Semi-Supervised Learning via Graph Filtering.
CVPR
Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, Zhichao Guan
2019 J jnl
Network Transfer Learning via Adversarial Domain Adaptation with Graph Convolution.
CoRR
Quanyu Dai, Xiao Shen, Xiao-Ming Wu, Dan Wang
2019 — conf
Reconstructing Capsule Networks for Zero-shot Intent Classification.
EMNLP/IJCNLP (1)
Han Liu, Xiaotong Zhang, Lu Fan, Xuandi Fu, Qimai Li, Xiao-Ming Wu, Albert Y. S. Lam
2019 J jnl
Variational Metric Scaling for Metric-Based Meta-Learning.
CoRR
Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung
2018 A* conf
Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning.
AAAI
Qimai Li, Zhichao Han, Xiao-Ming Wu
2018 J jnl
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning.
CoRR
Qimai Li, Zhichao Han, Xiao-Ming Wu
2018 J jnl
Large Margin Few-Shot Learning.
CoRR
Yong Wang, Xiao-Ming Wu, Qimai Li, Jiatao Gu, Wangmeng Xiang, Lei Zhang, Victor O. K. Li
2015 A* conf
New insights into Laplacian similarity search.
CVPR
Xiao-Ming Wu, Zhenguo Li, Shih-Fu Chang
2014 A* conf
Locally Linear Hashing for Extracting Non-linear Manifolds.
CVPR
Go Irie, Zhenguo Li, Xiao-Ming Wu, Shih-Fu Chang
2013 — conf
Analyzing the Harmonic Structure in Graph-Based Learning.
NIPS
Xiao-Ming Wu, Zhenguo Li, Shih-Fu Chang
2012 — conf
Learning with Partially Absorbing Random Walks.
NIPS
Xiao-Ming Wu, Zhenguo Li, Anthony Man-Cho So, John Wright, Shih-Fu Chang
2012 A* conf
Segmentation using superpixels: A bipartite graph partitioning approach.
CVPR
Zhenguo Li, Xiao-Ming Wu, Shih-Fu Chang
2009 — conf
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite-Quadratic-Linear Programming.
NIPS
Xiao-Ming Wu, Anthony Man-Cho So, Zhenguo Li, Shuo-Yen Robert Li