| 2026 | ACL | FOREVER: Forgetting Curve-Inspired Memory Replay for Language Model Continual Learning. | Yujie Feng, Hao Wang, Jian Li, Xu Chu, Zhaolu Kang, Yiran Liu, Yasha Wang, Philip S. Yu, Xiao-Ming Wu |
| 2026 | ACL | MSEarth: A Multimodal Benchmark for Earth Science Phenomenon Discovery with MLLMs. | Xiangyu Zhao, Wanghan Xu, Bo Liu, Yuhao Zhou, Fenghua Ling, Ben Fei, Xiaoyu Yue, Lei Bai, Wenlong Zhang, Xiao-Ming Wu |
| 2026 | PAKDD | Learning Multi-aspect Item Palette: A Semantic Tokenization Framework for Generative Recommendation. | Qijiong Liu, Jieming Zhu, Zhaocheng Du, Lu Fan, Zhou Zhao, Xiao-Ming Wu |
| 2026 | SIGIR | Full Retraining, Incremental Fine-tuning, and Hybrid Serving: Model Updating and Serving for Industrial Generative Recommender Systems. | Lu Fan, Qijiong Liu, Zhongzhou Liu, Guoyuan An, Wei Guo, Yong Liu, Xiao-Ming Wu |
| 2026 | WSDM | Mitigating the Threshold Priming Effect in Large Language Model-Based Relevance Judgments via Personality Simulation. | Nuo Chen, Hanpei Fang, Jiqun Liu, Wilson Wei, Tetsuya Sakai, Xiao-Ming Wu |
| 2026 | WSDM | Accelerating Generative Recommendation via Simple Categorical User Sequence Compression. | Qijiong Liu, Lu Fan, Zhongzhou Liu, Xiaoyu Dong, Yuankai Luo, Guoyuan An, Nuo Chen, Wei Guo, Yong Liu, Xiao-Ming Wu |
| 2025 | AAAI | Dynamic Spectral Graph Anomaly Detection. | Jianbo Zheng, Chao Yang, Tairui Zhang, Longbing Cao, Bin Jiang, Xuhui Fan, Xiao-Ming Wu, Xianxun Zhu |
| 2025 | ACL | Recurrent Knowledge Identification and Fusion for Language Model Continual Learning. | Yujie Feng, Xujia Wang, Zexin Lu, Shenghong Fu, Guangyuan Shi, Yongxin Xu, Yasha Wang, Philip S. Yu, Xu Chu, Xiao-Ming Wu |
| 2025 | CVPR | Panorama Generation From NFoV Image Done Right. | Dian Zheng, Cheng Zhang, Xiao-Ming Wu, Cao Li, Chengfei Lv, Jian-Fang Hu, Wei-Shi Zheng |
| 2025 | EMNLP | AIMMerging: Adaptive Iterative Model Merging Using Training Trajectories for Language Model Continual Learning. | Yujie Feng, Jian Li, Xiaoyu Dong, Pengfei Xu, Xiaohui Zhou, Yujia Zhang, Zexin Lu, Yasha Wang, Alan Zhao, Xu Chu, Xiao-Ming Wu |
| 2025 | EMNLP | GeoEdit: Geometric Knowledge Editing for Large Language Models. | Yujie Feng, Li-Ming Zhan, Zexin Lu, Yongxin Xu, Xu Chu, Yasha Wang, Jiannong Cao, Philip S. Yu, Xiao-Ming Wu |
| 2025 | ICCV | Rethinking Bimanual Robotic Manipulation: Learning with Decoupled Interaction Framework. | Jian-Jian Jiang, Xiao-Ming Wu, Yi-Xiang He, Ling-An Zeng, Yi-Lin Wei, Dandan Zhang, Wei-Shi Zheng |
| 2025 | ICCV | GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-Ray Diagnosis. | Bo Liu, Ke Zou, Li-Ming Zhan, Zexin Lu, Xiaoyu Dong, Yidi Chen, Chengqiang Xie, Jiannong Cao, Xiao-Ming Wu, Huazhu Fu |
| 2025 | ICCV | AffordDexGrasp: Open-Set Language-Guided Dexterous Grasp With Generalizable-Instructive Affordance. | Yi-Lin Wei, Mu Lin, Yuhao Lin, Jian-Jian Jiang, Xiao-Ming Wu, Ling-An Zeng, Wei-Shi Zheng |
| 2025 | ICCV | iManip: Skill-Incremental Learning for Robotic Manipulation. | Zexin Zheng, Jia-Feng Cai, Xiao-Ming Wu, Yi-Lin Wei, Yu-Ming Tang, Ancong Wu, Wei-Shi Zheng |
| 2025 | ICLR | Beyond Random Masking: When Dropout meets Graph Convolutional Networks. | Yuankai Luo, Xiao-Ming Wu, Hao Zhu |
| 2025 | ICLR | Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning. | Yuankai Luo, Hongkang Li, Qijiong Liu, Lei Shi, Xiao-Ming Wu |
| 2025 | ICLR | WeatherGFM: Learning a Weather Generalist Foundation Model via In-context Learning. | Xiangyu Zhao, Zhiwang Zhou, Wenlong Zhang, Yihao Liu, Xiangyu Chen, Junchao Gong, Hao Chen, Ben Fei, Shiqi Chen, Wanli Ouyang, Xiao-Ming Wu, Lei Bai |
| 2025 | ICML | Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet Excellence. | Yuankai Luo, Lei Shi, Xiao-Ming Wu |
| 2025 | ICRA | UGotMe: An Embodied System for Affective Human-Robot Interaction. | Pei-Zhen Li, Longbing Cao, Xiao-Ming Wu, Xiaohan Yu, Runze Yang |
| 2025 | WWW | MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising. | Quanyu Dai, Jiaren Xiao, Zhaocheng Du, Jieming Zhu, Chengxiao Luo, Xiao-Ming Wu, Zhenhua Dong |
| 2025 | WWW | Legommenders: A Comprehensive Content-Based Recommendation Library with LLM Support. | Qijiong Liu, Lu Fan, Xiao-Ming Wu |
| 2025 | WWW | Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation. | Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang |
| 2024 | AAAI | Correlation Matching Transformation Transformers for UHD Image Restoration. | Cong Wang, Jinshan Pan, Wei Wang, Gang Fu, Siyuan Liang, Mengzhu Wang, Xiao-Ming Wu, Jun Liu |
| 2024 | AAAI | SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency. | Cong Wang, Jinshan Pan, Wanyu Lin, Jiangxin Dong, Wei Wang, Xiao-Ming Wu |
| 2024 | ACL | Continual Dialogue State Tracking via Reason-of-Select Distillation. | Yujie Feng, Bo Liu, Xiaoyu Dong, Zexin Lu, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam |
| 2024 | ACL | TaSL: Continual Dialog State Tracking via Task Skill Localization and Consolidation. | Yujie Feng, Xu Chu, Yongxin Xu, Guangyuan Shi, Bo Liu, Xiao-Ming Wu |
| 2024 | ACL | EasyGen: Easing Multimodal Generation with BiDiffuser and LLMs. | Xiangyu Zhao, Bo Liu, Qijiong Liu, Guangyuan Shi, Xiao-Ming Wu |
| 2024 | COLING | LANID: LLM-assisted New Intent Discovery. | Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu |
| 2024 | COLING | How Good Are LLMs at Out-of-Distribution Detection? | Bo Liu, Li-Ming Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu |
| 2024 | COLING | VI-OOD: A Unified Framework of Representation Learning for Textual Out-of-distribution Detection. | Li-Ming Zhan, Bo Liu, Xiao-Ming Wu |
| 2024 | CoRL | Real-to-Sim Grasp: Rethinking the Gap between Simulation and Real World in Grasp Detection. | Jia-Feng Cai, Zibo Chen, Xiao-Ming Wu, Jian-Jian Jiang, Yi-Lin Wei, Wei-Shi Zheng |
| 2024 | CVPR | Single-View Scene Point Cloud Human Grasp Generation. | Yan-Kang Wang, Chengyi Xing, Yi-Lin Wei, Xiao-Ming Wu, Wei-Shi Zheng |
| 2024 | CVPR | Dexterous Grasp Transformer. | Guo-Hao Xu, Yi-Lin Wei, Dian Zheng, Xiao-Ming Wu, Wei-Shi Zheng |
| 2024 | CVPR | Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model. | Dian Zheng, Xiao-Ming Wu, Shuzhou Yang, Jian Zhang, Jian-Fang Hu, Wei-Shi Zheng |
| 2024 | ECCV | An Economic Framework for 6-DoF Grasp Detection. | Xiao-Ming Wu, Jia-Feng Cai, Jian-Jian Jiang, Dian Zheng, Yi-Lin Wei, Wei-Shi Zheng |
| 2024 | EMNLP | Zero-shot Cross-domain Dialogue State Tracking via Context-aware Auto-prompting and Instruction-following Contrastive Decoding. | Xiaoyu Dong, Yujie Feng, Zexin Lu, Guangyuan Shi, Xiao-Ming Wu |
| 2024 | EMNLP | UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation. | Xiangyu Zhao, Yuehan Zhang, Wenlong Zhang, Xiao-Ming Wu |
| 2024 | ICLR | SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution. | Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Xiaoyun Zhang, Yu Qiao, Xiao-Ming Wu, Chao Dong |
| 2024 | ICML | Easing Concept Bleeding in Diffusion via Entity Localization and Anchoring. | Jiewei Zhang, Song Guo, Peiran Dong, Jie Zhang, Ziming Liu, Yue Yu, Xiao-Ming Wu |
| 2024 | ICPR | iGrasp: An Interactive 2D-3D Framework for 6-DoF Grasp Detection. | Jian-Jian Jiang, Xiao-Ming Wu, Zibo Chen, Yi-Lin Wei, Wei-Shi Zheng |
| 2024 | KDD | Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. | Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong |
| 2024 | WWW | Discrete Semantic Tokenization for Deep CTR Prediction. | Qijiong Liu, Hengchang Hu, Jiahao Wu, Jieming Zhu, Min-Yen Kan, Xiao-Ming Wu |
| 2024 | WWW | Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization. | Qijiong Liu, Jiaren Xiao, Lu Fan, Jieming Zhu, Xiao-Ming Wu |
| 2024 | WWW | Benchmarking News Recommendation in the Era of Green AI. | Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu |
| 2024 | WSDM | ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models. | Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu |
| 2023 | AAAI | Boosting Few-Shot Text Classification via Distribution Estimation. | Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Fenglong Ma, Xiao-Ming Wu, Hongyang Chen, Hong Yu, Xianchao Zhang |
| 2023 | AAAI | Continual Graph Convolutional Network for Text Classification. | Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding |
| 2023 | ACL | Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training. | Haode Zhang, Haowen Liang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam |
| 2023 | CVPR | Generating Anomalies for Video Anomaly Detection with Prompt-based Feature Mapping. | Zuhao Liu, Xiao-Ming Wu, Dian Zheng, Kun-Yu Lin, Wei-Shi Zheng |
| 2023 | EMNLP | Towards LLM-driven Dialogue State Tracking. | Yujie Feng, Zexin Lu, Bo Liu, Liming Zhan, Xiao-Ming Wu |
| 2023 | ICCV | Estimator Meets Equilibrium Perspective: A Rectified Straight Through Estimator for Binary Neural Networks Training. | Xiao-Ming Wu, Dian Zheng, Zuhao Liu, Wei-Shi Zheng |
| 2023 | ICLR | Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning. | Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu |
| 2023 | WWW | FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation. | Qijiong Liu, Jieming Zhu, Jiahao Wu, Tiandeng Wu, Zhenhua Dong, Xiao-Ming Wu |
| 2023 | SIGIR | Neighborhood-based Hard Negative Mining for Sequential Recommendation. | Lu Fan, Jiashu Pu, Rongsheng Zhang, Xiao-Ming Wu |
| 2022 | AAAI | Online Enhanced Semantic Hashing: Towards Effective and Efficient Retrieval for Streaming Multi-Modal Data. | Xiao-Ming Wu, Xin Luo, Yu-Wei Zhan, Chenlu Ding, Zhen-Duo Chen, Xin-Shun Xu |
| 2022 | AAAI | Online-Updated High-Order Collaborative Networks for Single Image Deraining. | Cong Wang, Jinshan Pan, Xiao-Ming Wu |
| 2022 | ACL | New Intent Discovery with Pre-training and Contrastive Learning. | Yuwei Zhang, Haode Zhang, Li-Ming Zhan, Xiao-Ming Wu, Albert Y. S. Lam |
| 2022 | CIKM | Weakly-Supervised Online Hashing with Refined Pseudo Tags. | Chenlu Ding, Xin Luo, Xiao-Ming Wu, Yu-Wei Zhan, Rui Li, Hui Zhang, Xin-Shun Xu |
| 2022 | COLING | A Closer Look at Few-Shot Out-of-Distribution Intent Detection. | Li-Ming Zhan, Haowen Liang, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam |
| 2022 | CVPR | A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds. | Wenlong Zhang, Guangyuan Shi, Yihao Liu, Chao Dong, Xiao-Ming Wu |
| 2022 | NAACL | Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization. | Haode Zhang, Haowen Liang, Yuwei Zhang, Li-Ming Zhan, Xiao-Ming Wu, Xiaolei Lu, Albert Y. S. Lam |
| 2022 | WWW | Modeling User Behavior with Graph Convolution for Personalized Product Search. | Lu Fan, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang |
| 2021 | ACL | Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training. | Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam |
| 2021 | EMNLP | Effectiveness of Pre-training for Few-shot Intent Classification. | Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y. S. Lam |
| 2021 | KDD | Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs. | Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu |
| 2021 | KDD | Embedding-based Product Retrieval in Taobao Search. | Sen Li, Fuyu Lv, Taiwei Jin, Guli Lin, Keping Yang, Xiaoyi Zeng, Xiao-Ming Wu, Qianli Ma |
| 2021 | MICCAI | Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images. | Bo Liu, Li-Ming Zhan, Xiao-Ming Wu |
| 2020 | AAAI | Variational Metric Scaling for Metric-Based Meta-Learning. | Jiaxin Chen, Li-Ming Zhan, Xiao-Ming Wu, Fu-Lai Chung |
| 2020 | ACL | Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification. | Guangfeng Yan, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Xiao-Ming Wu, Albert Y. S. Lam |
| 2020 | KDD | M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems. | Menghan Wang, Yujie Lin, Guli Lin, Keping Yang, Xiao-Ming Wu |
| 2019 | CVPR | Label Efficient Semi-Supervised Learning via Graph Filtering. | Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, Zhichao Guan |
| 2019 | EMNLP | Reconstructing Capsule Networks for Zero-shot Intent Classification. | Han Liu, Xiaotong Zhang, Lu Fan, Xuandi Fu, Qimai Li, Xiao-Ming Wu, Albert Y. S. Lam |
| 2019 | IJCAI | Attributed Graph Clustering via Adaptive Graph Convolution. | Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu |
| 2018 | AAAI | Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning. | Qimai Li, Zhichao Han, Xiao-Ming Wu |
| 2015 | CVPR | New insights into Laplacian similarity search. | Xiao-Ming Wu, Zhenguo Li, Shih-Fu Chang |
| 2014 | CVPR | Locally Linear Hashing for Extracting Non-linear Manifolds. | Go Irie, Zhenguo Li, Xiao-Ming Wu, Shih-Fu Chang |
| 2014 | ICARCV | A novel routing recovery strategy based on particle swarm algorithm for wireless sensor networks with multiple mobile sinks. | Yifan Hu, Xiao-Ming Wu, Fuqiang Wang, Xiangzhi Liu, Hua Han |
| 2012 | CVPR | Segmentation using superpixels: A bipartite graph partitioning approach. | Zhenguo Li, Xiao-Ming Wu, Shih-Fu Chang |