Stepwise-Decomposable Influence Diagrams. - Nevin Lianwen Zhang; David L. Poole (KR, 1992)

Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams. - Nevin Lianwen Zhang; Runping Qi; David L. Poole (UAI, 1993)

Solving Asymmetric Decision Problems with Influence Diagrams. - Runping Qi; Nevin Lianwen Zhang; David L. Poole (UAI, 1994)

Intercausal Independence and Heterogeneous Factorization. - Nevin Lianwen Zhang; David L. Poole (UAI, 1994)

A computational theory of decision networks. - Nevin Lianwen Zhang; Runping Qi; David L. Poole (Int. J. Approx. Reason., 1994)

Inference with Causal Independence in the CPSC Network. - Nevin Lianwen Zhang (UAI, 1995)

Irrelevance and ParameterLearning in Bayesian Networks. - Nevin Lianwen Zhang (Artif. Intell., 1996)

Exploiting Causal Independence in Bayesian Network Inference. - Nevin Lianwen Zhang; David L. Poole (J. Artif. Intell. Res., 1996)

Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes. - Anthony R. Cassandra; Michael L. Littman; Nevin Lianwen Zhang (UAI, 1997)

Region-Based Approximations for Planning in Stochastic Domains. - Nevin Lianwen Zhang; Wenju Liu (UAI, 1997)

Fast Value Iteration for Goal-Directed Markov Decision Processes. - Nevin Lianwen Zhang; Weihong Zhang (UAI, 1997)

A Model Approximation Scheme for Planning in Partially Observable Stochastic Domains. - Nevin Lianwen Zhang; Wenju Liu (J. Artif. Intell. Res., 1997)

Context-Specific Independence, Decomposition of Conditional Probabilities, and Inference in Bayesian Networks. - Nevin Lianwen Zhang (PRICAI, 1998)

Planning with Partially Observable Markov Decision Processes: Advances in Exact Solution Method. - Nevin Lianwen Zhang; Stephen S. Lee (UAI, 1998)

Computational Properties of Two Exact Algorithms for Bayesian Networks. - Nevin Lianwen Zhang (Appl. Intell., 1998)

Probabilistic Inference in Influence Diagrams. - Nevin Lianwen Zhang (Comput. Intell., 1998)

Independence of causal influence and clique tree propagation. - Nevin Lianwen Zhang; Li Yan (Int. J. Approx. Reason., 1998)

On the Role of Context-Specific Independence in Probabilistic Inference. - Nevin Lianwen Zhang; David L. Poole (IJCAI, 1999)

An Environment Model for Nonstationary Reinforcement Learning. - Samuel P. M. Choi; Dit-Yan Yeung; Nevin Lianwen Zhang (NIPS, 1999)

A Method for Speeding Up Value Iteration in Partially Observable Markov Decision Processes. - Nevin Lianwen Zhang; Stephen S. Lee; Weihong Zhang (UAI, 1999)

Solving Hidden-Mode Markov Decision Problems. - Samuel Ping-Man Choi; Nevin Lianwen Zhang; Dit-Yan Yeung (AISTATS, 2001)

Space-Progressive Value Iteration: An Anytime Algorithm for a Class of POMDPs. - Nevin Lianwen Zhang; Weihong Zhang (ECSQARU, 2001)

Hidden-Mode Markov Decision Processes for Nonstationary Sequential Decision Making. - Samuel P. M. Choi; Dit-Yan Yeung; Nevin Lianwen Zhang (Sequence Learning, 2001)

Speeding Up the Convergence of Value Iteration in Partially Observable Markov Decision Processes. - Nevin Lianwen Zhang; Weihong Zhang (J. Artif. Intell. Res., 2001)

Value Iteration Working with Belief Subset. - Weihong Zhang; Nevin Lianwen Zhang (AAAI/IAAI, 2002)

An Alternative Formulation of Dynamic-Programming Updates for POMDPs. - Weihong Zhang; Nevin Lianwen Zhang (AI&M, 2002)

Dimension Correction for Hierarchical Latent Class Models. - Tomás Kocka; Nevin Lianwen Zhang (UAI, 2002)

Inference in Bayesian Networks: The Role of Context-Specific Independence. - Nevin Lianwen Zhang (Int. J. Inf. Technol. Decis. Mak., 2002)

Effective Dimensions of Partially Observed Polytrees. - Tomás Kocka; Nevin Lianwen Zhang (ECSQARU, 2003)

Exploiting Contextual Independence In Probabilistic Inference. - David L. Poole; Nevin Lianwen Zhang (J. Artif. Intell. Res., 2003)

Reinforcement Learning in Episodic Non-stationary Markovian Environments. - Samuel P. M. Choi; Nevin Lianwen Zhang; Dit-Yan Yeung (IC-AI, 2004)

Efficient Learning of Hierarchical Latent Class Models. - Nevin Lianwen Zhang; Tomás Kocka (ICTAI, 2004)

Latent variable discovery in classification models. - Nevin Lianwen Zhang; Thomas D. Nielsen; Finn Verner Jensen (Artif. Intell. Medicine, 2004)

Effective Dimensions of Hierarchical Latent Class Models. - Nevin Lianwen Zhang; Tomás Kocka (J. Artif. Intell. Res., 2004)

Hierarchical Latent Class Models for Cluster Analysis. - Nevin Lianwen Zhang (J. Mach. Learn. Res., 2004)

Effective dimensions of partially observed polytrees. - Tao Chen; Tomás Kocka; Nevin Lianwen Zhang (Int. J. Approx. Reason., 2005)

Special Issue on ECSQARU-2003: The Seventh European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty: Message from the Guest Editors. - Thomas D. Nielsen; Nevin Lianwen Zhang (Int. J. Approx. Reason., 2005)

Restricted Value Iteration: Theory and Algorithms. - Weihong Zhang; Nevin Lianwen Zhang (J. Artif. Intell. Res., 2005)

Quartet-Based Learning of Hierarchical Latent Class Models: Discovery of Shallow Latent Variables. - Tao Chen; Nevin Lianwen Zhang (AI&M, 2006)

Quartet-Based Learning of Shallow Latent Variables. - Tao Chen; Nevin Lianwen Zhang (Probabilistic Graphical Models, 2006)

Severity of Local Maxima for the EM Algorithm: Experiences with Hierarchical Latent Class Models. - Yi Wang 006; Nevin Lianwen Zhang (Probabilistic Graphical Models, 2006)

Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine. - Nevin Lianwen Zhang; Shihong Yuan; Tao Chen; Yi Wang 006 (AIME, 2007)

Discovering Latent Structures: Experience with the CoIL Challenge 2000 Data Set. - Nevin Lianwen Zhang (International Conference on Computational Science (4), 2007)

Latent tree models and diagnosis in traditional Chinese medicine. - Nevin Lianwen Zhang; Shihong Yuan; Tao Chen; Yi Wang 006 (Artif. Intell. Medicine, 2008)

Latent Tree Models and Approximate Inference in Bayesian Networks. - Yi Wang 006; Nevin Lianwen Zhang; Tao Chen (J. Artif. Intell. Res., 2008)

Discovery of latent structures: Experience with the CoIL Challenge 2000 data set. - Nevin Lianwen Zhang; Yi Wang 006; Tao Chen (J. Syst. Sci. Complex., 2008)

Weights of Evidence and Internal Conflict for Support Functions. - Nevin Lianwen Zhang (Classic Works of the Dempster-Shafer Theory of Belief Functions, 2008)

Statistical truths in traditional Chinese medicine theories. - Nevin L. Zhang; Shihong Yuan (BIBM Workshops, 2010)

Variable Selection in Model-Based Clustering: To Do or To Facilitate. - Leonard K. M. Poon; Nevin Lianwen Zhang; Tao Chen; Yi Wang 006 (ICML, 2010)

The Role of Operation Granularity in Search-Based Learning of Latent Tree Models. - Tao Chen; Nevin Lianwen Zhang; Yi Wang 006 (JSAI-isAI Workshops, 2010)

Latent Tree Classifier. - Yi Wang 006; Nevin Lianwen Zhang; Tao Chen; Leonard K. M. Poon (ECSQARU, 2011)

Fast Multidimensional Clustering of Categorical Data. - Tengfei Liu; Nevin Lianwen Zhang; Kin Man Poon; Yi Wang 006; Hua Liu (MultiClust@ECML/PKDD, 2011)

Discovery of Regularities in the Use of Herbs in Traditional Chinese Medicine Prescriptions. - Nevin Lianwen Zhang; Runsun Zhang; Tao Chen (PAKDD Workshops, 2011)

A Model-Based Approach to Rounding in Spectral Clustering. - Leonard K. M. Poon; April H. Liu; Tengfei Liu; Nevin Lianwen Zhang (UAI, 2012)

Model-based multidimensional clustering of categorical data. - Tao Chen; Nevin Lianwen Zhang; Tengfei Liu; Kin Man Poon; Yi Wang 006 (Artif. Intell., 2012)

Inter-causal Independence and Heterogeneous Factorization - Nevin Lianwen Zhang; David L. Poole (CoRR, 2013)

Sidestepping the Triangulation Problem in Bayesian Net Computations - Nevin Lianwen Zhang; David L. Poole (CoRR, 2013)

Model-based clustering of high-dimensional data: Variable selection versus facet determination. - Leonard K. M. Poon; Nevin Lianwen Zhang; Tengfei Liu; April H. Liu (Int. J. Approx. Reason., 2013)

LTC: A latent tree approach to classification. - Yi Wang 006; Nevin Lianwen Zhang; Tao Chen; Leonard K. M. Poon (Int. J. Approx. Reason., 2013)

A Survey on Latent Tree Models and Applications. - Raphaël Mourad; Christine Sinoquet; Nevin Lianwen Zhang; Tengfei Liu; Philippe Leray 001 (J. Artif. Intell. Res., 2013)

A Study of Recently Discovered Equalities about Latent Tree Models Using Inverse Edges. - Nevin Lianwen Zhang; Xiaofei Wang; Peixian Chen (Probabilistic Graphical Models, 2014)

Hierarchical Latent Tree Analysis for Topic Detection. - Tengfei Liu; Nevin Lianwen Zhang; Peixian Chen (ECML/PKDD (2), 2014)

An Evidence-Based Approach to Patient Classification in Traditional Chinese Medicine based on Latent Tree Analysis. - Nevin Lianwen Zhang; Chen Fu; Tengfei Liu; Kin Man Poon; Peixian Chen; Bao Xin Chen; Yun Ling Zhang (CoRR, 2014)

Latent tree models for rounding in spectral clustering. - April H. Liu; Leonard K. M. Poon; Tengfei Liu; Nevin Lianwen Zhang (Neurocomputing, 2014)

Unidimensional Clustering of Discrete Data Using Latent Tree Models. - April H. Liu; Leonard K. M. Poon; Nevin Lianwen Zhang (AAAI, 2015)

Bayesian adaptive matrix factorization with automatic model selection. - Peixian Chen; Naiyan Wang; Nevin L. Zhang; Dit-Yan Yeung (CVPR, 2015)

Greedy learning of latent tree models for multidimensional clustering. - Tengfei Liu; Nevin Lianwen Zhang; Peixian Chen; April Hua Liu; Leonard K. M. Poon; Yi Wang 006 (Mach. Learn., 2015)

Progressive EM for Latent Tree Models and Hierarchical Topic Detection. - Peixian Chen; Nevin L. Zhang; Leonard K. M. Poon; Zhourong Chen (AAAI, 2016)

Latent Tree Models for Hierarchical Topic Detection. - Peixian Chen; Nevin L. Zhang; Tengfei Liu; Leonard K. M. Poon; Zhourong Chen (CoRR, 2016)

Identification and classification of TCM syndrome types among patients with vascular mild cognitive impairment using latent tree analysis. - Chen Fu; Nevin L. Zhang; Bao Xin Chen; Zhourong Chen; Xiang Lan Jin; Rong Juan Guo; Zhi Gang Chen; Yun Ling Zhang (CoRR, 2016)

Topic Browsing for Research Papers with Hierarchical Latent Tree Analysis. - Leonard K. M. Poon; Nevin L. Zhang (CoRR, 2016)

Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis. - Zhourong Chen; Nevin L. Zhang; Dit-Yan Yeung; Peixian Chen (AAAI, 2017)

Latent Tree Analysis. - Nevin L. Zhang; Leonard K. M. Poon (AAAI, 2017)

Topic Browsing System for Research Papers Based on Hierarchical Latent Tree Analysis. - Leonard K. M. Poon; Chun Fai Leung; Peixian Chen; Nevin L. Zhang (APWeb/WAIM (2), 2017)

Mining Textual Reviews with Hierarchical Latent Tree Analysis. - Leonard K. M. Poon; Chun Fai Leung; Nevin L. Zhang (DMBD, 2017)

Latent tree models for hierarchical topic detection. - Peixian Chen; Nevin L. Zhang; Tengfei Liu; Leonard K. M. Poon; Zhourong Chen; Farhan Khawar (Artif. Intell., 2017)

Conformative Filtering for Implicit Feedback Data. - Farhan Khawar; Nevin L. Zhang; Jinxing Yu (CoRR, 2017)

Document Generation with Hierarchical Latent Tree Models. - Peixian Chen; Zhourong Chen; Nevin L. Zhang (CoRR, 2017)

Building Sparse Deep Feedforward Networks using Tree Receptive Fields. - Xiaopeng Li; Zhourong Chen; Nevin L. Zhang (IJCAI, 2018)

Latent Tree Variational Autoencoder for Joint Representation Learning and Multidimensional Clustering. - Xiaopeng Li; Zhourong Chen; Nevin L. Zhang (CoRR, 2018)

Learning Sparse Deep Feedforward Networks via Tree Skeleton Expansion. - Zhourong Chen; Xiaopeng Li; Nevin L. Zhang (CoRR, 2018)

Learning Hierarchical Item Categories from Implicit Feedback Data for Efficient Recommendations and Browsing. - Farhan Khawar; Nevin L. Zhang (CoRR, 2018)

Matrix Factorization Equals Efficient Co-occurrence Representation. - Farhan Khawar; Nevin L. Zhang (CoRR, 2018)

Using Taste Groups for Collaborative Filtering. - Farhan Khawar; Nevin L. Zhang (CoRR, 2018)

UC-LTM: Unidimensional clustering using latent tree models for discrete data. - Leonard K. M. Poon; April H. Liu; Nevin L. Zhang (Int. J. Approx. Reason., 2018)

Learning to Abstract for Memory-augmented Conversational Response Generation. - Zhiliang Tian; Wei Bi; Xiaopeng Li; Nevin L. Zhang (ACL (1), 2019)

Conformative Filtering for Implicit Feedback Data. - Farhan Khawar; Nevin L. Zhang (ECIR (1), 2019)

A Novel Document Generation Process for Topic Detection Based on Hierarchical Latent Tree Models. - Peixian Chen; Zhourong Chen; Nevin L. Zhang (ECSQARU, 2019)

Fast Structure Learning for Deep Feedforward Networks via Tree Skeleton Expansion. - Zhourong Chen; Xiaopeng Li; Zhiliang Tian; Nevin L. Zhang (ECSQARU, 2019)

Modeling Multidimensional User Preferences for Collaborative Filtering. - Farhan Khawar; Nevin L. Zhang (ICDE, 2019)

Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering. - Xiaopeng Li; Zhourong Chen; Leonard K. M. Poon; Nevin L. Zhang (ICLR (Poster), 2019)

Cleaned Similarity for Better Memory-Based Recommenders. - Farhan Khawar; Nevin L. Zhang (SIGIR, 2019)

Not All Attention Is Needed: Gated Attention Network for Sequence Data. - Lanqing Xue; Xiaopeng Li; Nevin L. Zhang (AAAI, 2020)

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 (ACL, 2020)

Learning the Structure of Auto-Encoding Recommenders. - Farhan Khawar; Leonard K. M. Poon; Nevin L. Zhang (WWW, 2020)

Handling Collocations in Hierarchical Latent Tree Analysis for Topic Modeling. - Leonard K. M. Poon; Nevin L. Zhang; Haoran Xie 001; Gary Cheng 001 (CoRR, 2020)

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 (AAAI, 2021)

Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization. - Dongkyu Lee; Zhiliang Tian; Lanqing Xue; Nevin L. Zhang (ACL/IJCNLP (1), 2021)

DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. - Lanqing Xue; Kaitao Song; Duocai Wu; Xu Tan 003; Nevin L. Zhang; Tao Qin 001; Wei-Qiang Zhang; Tie-Yan Liu (ACL/IJCNLP (1), 2021)

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 021; Nevin L. Zhang (ACL (1), 2022)

Emotion-Aware Multimodal Pre-training for Image-Grounded Emotional Response Generation. - Zhiliang Tian; Zhihua Wen; Zhenghao Wu; Yiping Song; Jintao Tang; Dongsheng Li 001; Nevin L. Zhang (DASFAA (3), 2022)

Adaptive Label Smoothing with Self-Knowledge in Natural Language Generation. - Dongkyu Lee; Ka Chun Cheung; Nevin L. Zhang (EMNLP, 2022)

Hard Gate Knowledge Distillation - Leverage Calibration for Robust and Reliable Language Model. - Dongkyu Lee; Zhiliang Tian; Yingxiu Zhao; Ka Chun Cheung; Nevin Lianwen Zhang (EMNLP, 2022)

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 001; Nevin L. Zhang (EMNLP (Findings), 2022)

Semi-Supervised Lifelong Language Learning. - Yingxiu Zhao; Yinhe Zheng; Bowen Yu 002; Zhiliang Tian; Dongkyu Lee; Jian Sun 021; Yongbin Li; Nevin L. Zhang (EMNLP (Findings), 2022)

Prompt Conditioned VAE: Enhancing Generative Replay for Lifelong Learning in Task-Oriented Dialogue. - Yingxiu Zhao; Yinhe Zheng; Zhiliang Tian; Chang Gao; Jian Sun 021; Nevin L. Zhang (EMNLP, 2022)

SeqPATE: Differentially Private Text Generation via Knowledge Distillation. - Zhiliang Tian; Yingxiu Zhao; Ziyue Huang; Yu-Xiang Wang 003; Nevin L. Zhang; He He (NeurIPS, 2022)

Example Perplexity. - Nevin L. Zhang; Weiyan Xie; Zhi Lin; Guanfang Dong; Xiao-Hui Li 009; Caleb Chen Cao; Yunpeng Wang (CoRR, 2022)

Deep Clustering with Features from Self-Supervised Pretraining. - Xingzhi Zhou 002; Nevin L. Zhang (CoRR, 2022)

Prompt Conditioned VAE: Enhancing Generative Replay for Lifelong Learning in Task-Oriented Dialogue. - Yingxiu Zhao; Yinhe Zheng; Zhiliang Tian; Chang Gao; Bowen Yu 002; Haiyang Yu 003; Yongbin Li; Jian Sun 021; Nevin L. Zhang (CoRR, 2022)

Semi-Supervised Lifelong Language Learning. - Yingxiu Zhao; Yinhe Zheng; Bowen Yu 002; Zhiliang Tian; Dongkyu Lee; Jian Sun 021; Haiyang Yu 003; Yongbin Li; Nevin L. Zhang (CoRR, 2022)

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 (ACL (Findings), 2023)

Causal Document-Grounded Dialogue Pre-training. - Yingxiu Zhao; Bowen Yu 002; Bowen Li 002; Haiyang Yu 003; Jinyang Li 003; Chao Wang; Fei Huang 002; Yongbin Li; Nevin L. Zhang (EMNLP, 2023)

ViT-CX: Causal Explanation of Vision Transformers. - Weiyan Xie; Xiao-Hui Li 009; Caleb Chen Cao; Nevin L. Zhang (IJCAI, 2023)

Two-stage holistic and contrastive explanation of image classification. - Weiyan Xie; Xiao-Hui Li 009; Zhi Lin; Leonard K. M. Poon; Caleb Chen Cao; Nevin L. Zhang (UAI, 2023)

Contrastive Domain Generalization via Logit Attribution Matching. - Han Gao; Kaican Li; Yongxiang Huang; Luning Wang; Caleb Chen Cao; Nevin L. Zhang (CoRR, 2023)

A Causal Framework to Unify Common Domain Generalization Approaches. - Nevin L. Zhang; Kaican Li; Han Gao; Weiyan Xie; Zhi Lin; Zhenguo Li; Luning Wang; Yongxiang Huang (CoRR, 2023)

A Preliminary Study of the Intrinsic Relationship between Complexity and Alignment. - Yingxiu Zhao; Bowen Yu 002; Binyuan Hui; Haiyang Yu 003; Fei Huang 002; Yongbin Li; Nevin L. Zhang (CoRR, 2023)

Robustness May be More Brittle than We Think under Different Degrees of Distribution Shifts. - Kaican Li; Yifan Zhang; Lanqing Hong; Zhenguo Li; Nevin L. Zhang (CoRR, 2023)

TCM-FTP: Fine-Tuning Large Language Models for Herbal Prescription Prediction. - Xingzhi Zhou 002; Xin Dong; Chunhao Li; Yuning Bai; Yulong Xu; Ka Chun Cheung; Simon See; Xinpeng Song; Runshun Zhang; Xuezhong Zhou; Nevin L. Zhang (BIBM, 2024)

Tree-Instruct: A Preliminary Study of the Intrinsic Relationship between Complexity and Alignment. - Yingxiu Zhao; Bowen Yu 002; Binyuan Hui; Haiyang Yu 003; Minghao Li; Fei Huang 002; Nevin L. Zhang; Yongbin Li (LREC/COLING, 2024)

Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models. - Kaican Li; Weiyan Xie; Yongxiang Huang; Didan Deng; Lanqing Hong; Zhenguo Li; Ricardo Silva 001; Nevin L. Zhang (NeurIPS, 2024)

Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense. - Rui Min; Zeyu Qin; Nevin L. Zhang; Li Shen 008; Minhao Cheng (NeurIPS, 2024)

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 (UAI, 2024)

Resilient Practical Test-Time Adaptation: Soft Batch Normalization Alignment and Entropy-driven Memory Bank. - Xingzhi Zhou 002; Zhiliang Tian; Ka Chun Cheung; Simon See; Nevin L. Zhang (CoRR, 2024)

Breaking the mold: The challenge of large scale MARL specialization. - Stefan Juang; Hugh Cao; Arielle Zhou; Ruochen Liu; Nevin L. Zhang; Elvis S. Liu (CoRR, 2024)

Fine-Tuning Pre-trained Language Models for Robust Causal Representation Learning. - Jialin Yu; Yuxiang Zhou; Yulan He 001; Nevin L. Zhang; Ricardo Silva 001 (CoRR, 2024)

Test-Time Adaptation on Noisy Data via Model-Pruning-Based Filtering and Flatness-Aware Entropy Minimization. - Xingzhi Zhou 002; Zhiliang Tian; Boyang Zhang; Yibo Zhang; Ka Chun Cheung; Simon See; Hao Yang; Yun Zhou; Nevin L. Zhang (AAAI, 2025)

Resilient Test-Time Adaptation by Mitigating Batch-Normalization Overfitting. - Xingzhi Zhou 002; Boyang Zhang; Zhiliang Tian; Yibo Zhang; Xin Niu 002; Ka Chun Cheung; Simon See; Nevin L. Zhang (ICASSP, 2025)

CannyEdit: Selective Canny Control and Dual-Prompt Guidance for Training-Free Image Editing. - Weiyan Xie; Han Gao; Didan Deng; Kaican Li; April Hua Liu; Yongxiang Huang; Nevin L. Zhang (CoRR, 2025)