| 2025 | AAAI | Test-Time Adaptation on Noisy Data via Model-Pruning-Based Filtering and Flatness-Aware Entropy Minimization. | Xingzhi Zhou, Zhiliang Tian, Boyang Zhang, Yibo Zhang, Ka Chun Cheung, Simon See, Hao Yang, Yun Zhou, Nevin L. Zhang |
| 2025 | ICASSP | Resilient Test-Time Adaptation by Mitigating Batch-Normalization Overfitting. | Xingzhi Zhou, Boyang Zhang, Zhiliang Tian, Yibo Zhang, Xin Niu, Ka Chun Cheung, Simon See, Nevin L. Zhang |
| 2025 | ICML | COSDA: Counterfactual-based Susceptibility Risk Framework for Open-Set Domain Adaptation. | Wenxu Wang, Rui Zhou, Jing Wang, Yun Zhou, Cheng Zhu, Ruichun Tang, Bo Han, Nevin L. Zhang |
| 2024 | COLING | Tree-Instruct: A Preliminary Study of the Intrinsic Relationship between Complexity and Alignment. | Yingxiu Zhao, Bowen Yu, Binyuan Hui, Haiyang Yu, Minghao Li, Fei Huang, Nevin L. Zhang, Yongbin Li |
| 2024 | UAI | Consistency Regularization for Domain Generalization with Logit Attribution Matching. | Han Gao, Kaican Li, Weiyan Xie, Zhi Lin, Yongxiang Huang, Luning Wang, Caleb Chen Cao, Nevin L. Zhang |
| 2023 | ACL | Local Temperature Beam Search: Avoid Neural Text DeGeneration via Enhanced Calibration. | Dongkyu Lee, Gyeonghun Kim, Janghoon Han, Taesuk Hong, Yireun Kim, Stanley Jungkyu Choi, Nevin L. Zhang |
| 2023 | EMNLP | Causal Document-Grounded Dialogue Pre-training. | Yingxiu Zhao, Bowen Yu, Bowen Li, Haiyang Yu, Jinyang Li, Chao Wang, Fei Huang, Yongbin Li, Nevin L. Zhang |
| 2023 | IJCAI | ViT-CX: Causal Explanation of Vision Transformers. | Weiyan Xie, Xiao-Hui Li, Caleb Chen Cao, Nevin L. Zhang |
| 2023 | UAI | Two-stage holistic and contrastive explanation of image classification. | Weiyan Xie, Xiao-Hui Li, Zhi Lin, Leonard K. M. Poon, Caleb Chen Cao, Nevin L. Zhang |
| 2022 | ACL | Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation. | Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao, Yinhe Zheng, Dongkyu Lee, Yiping Song, Jian Sun, Nevin L. Zhang |
| 2022 | DASFAA | Emotion-Aware Multimodal Pre-training for Image-Grounded Emotional Response Generation. | Zhiliang Tian, Zhihua Wen, Zhenghao Wu, Yiping Song, Jintao Tang, Dongsheng Li, Nevin L. Zhang |
| 2022 | EMNLP | Adaptive Label Smoothing with Self-Knowledge in Natural Language Generation. | Dongkyu Lee, Ka Chun Cheung, Nevin L. Zhang |
| 2022 | EMNLP | Empathetic and Emotionally Positive Conversation Systems with an Emotion-specific Query-Response Memory. | Zhiliang Tian, Yinliang Wang, Yiping Song, Chi Zhang, Dongkyu Lee, Yingxiu Zhao, Dongsheng Li, Nevin L. Zhang |
| 2022 | EMNLP | Semi-Supervised Lifelong Language Learning. | Yingxiu Zhao, Yinhe Zheng, Bowen Yu, Zhiliang Tian, Dongkyu Lee, Jian Sun, Yongbin Li, Nevin L. Zhang |
| 2022 | EMNLP | Prompt Conditioned VAE: Enhancing Generative Replay for Lifelong Learning in Task-Oriented Dialogue. | Yingxiu Zhao, Yinhe Zheng, Zhiliang Tian, Chang Gao, Jian Sun, Nevin L. Zhang |
| 2021 | AAAI | Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks. | Zhiliang Tian, Wei Bi, Zihan Zhang, Dongkyu Lee, Yiping Song, Nevin L. Zhang |
| 2021 | ACL | Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization. | Dongkyu Lee, Zhiliang Tian, Lanqing Xue, Nevin L. Zhang |
| 2021 | ACL | DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. | Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu |
| 2020 | AAAI | Not All Attention Is Needed: Gated Attention Network for Sequence Data. | Lanqing Xue, Xiaopeng Li, Nevin L. Zhang |
| 2020 | ACL | Response-Anticipated Memory for On-Demand Knowledge Integration in Response Generation. | Zhiliang Tian, Wei Bi, Dongkyu Lee, Lanqing Xue, Yiping Song, Xiaojiang Liu, Nevin L. Zhang |
| 2020 | WWW | Learning the Structure of Auto-Encoding Recommenders. | Farhan Khawar, Leonard K. M. Poon, Nevin L. Zhang |
| 2019 | ACL | Learning to Abstract for Memory-augmented Conversational Response Generation. | Zhiliang Tian, Wei Bi, Xiaopeng Li, Nevin L. Zhang |
| 2019 | ECIR | Conformative Filtering for Implicit Feedback Data. | Farhan Khawar, Nevin L. Zhang |
| 2019 | ECSQARU | A Novel Document Generation Process for Topic Detection Based on Hierarchical Latent Tree Models. | Peixian Chen, Zhourong Chen, Nevin L. Zhang |
| 2019 | ECSQARU | Fast Structure Learning for Deep Feedforward Networks via Tree Skeleton Expansion. | Zhourong Chen, Xiaopeng Li, Zhiliang Tian, Nevin L. Zhang |
| 2019 | ICDE | Modeling Multidimensional User Preferences for Collaborative Filtering. | Farhan Khawar, Nevin L. Zhang |
| 2019 | ICLR | Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering. | Xiaopeng Li, Zhourong Chen, Leonard K. M. Poon, Nevin L. Zhang |
| 2019 | SIGIR | Cleaned Similarity for Better Memory-Based Recommenders. | Farhan Khawar, Nevin L. Zhang |
| 2018 | IJCAI | Building Sparse Deep Feedforward Networks using Tree Receptive Fields. | Xiaopeng Li, Zhourong Chen, Nevin L. Zhang |
| 2017 | AAAI | Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis. | Zhourong Chen, Nevin L. Zhang, Dit-Yan Yeung, Peixian Chen |
| 2017 | AAAI | Latent Tree Analysis. | Nevin L. Zhang, Leonard K. M. Poon |
| 2017 | APWEB | Topic Browsing System for Research Papers Based on Hierarchical Latent Tree Analysis. | Leonard K. M. Poon, Chun Fai Leung, Peixian Chen, Nevin L. Zhang |
| 2016 | AAAI | Progressive EM for Latent Tree Models and Hierarchical Topic Detection. | Peixian Chen, Nevin L. Zhang, Leonard K. M. Poon, Zhourong Chen |
| 2015 | CVPR | Bayesian adaptive matrix factorization with automatic model selection. | Peixian Chen, Naiyan Wang, Nevin L. Zhang, Dit-Yan Yeung |