Wavelet Image Compression Based on Context Predicting With Past Information in Rows (Columns). - Xiaoyuan Yang 003; Hui Ren; Bo Li 006; Zhengzhang Chen (ICNC (4), 2007)

The Study on Software Optimization Technology of Remote Sensing Image Compression System Based on DSP Platform. - Zhengzhang Chen; Bo Li 006; Feifei Zhou; Xiaoyuan Yang 003; Qian Wang; Yong Shi (MSA, 2007)

Detecting and Tracking Community Dynamics in Evolutionary Networks. - Zhengzhang Chen; Kevin A. Wilson; Ye Jin; William Hendrix; Nagiza F. Samatova (ICDM Workshops, 2010)

Inapproximability results for equations over infinite groups. - Wenbin Chen 002; Dengpan Yin; Zhengzhang Chen (Theor. Comput. Sci., 2010)

Detecting Pathway Cross-Talks by Analyzing Conserved Functional Modules across Multiple Phenotype-Expressing Organisms. - Kevin A. Wilson; Andrea M. Rocha; Kanchana Padmanabhan; Kuangyu Wang; Zhengzhang Chen; Ye Jin; James R. Mihelcic; Nagiza F. Samatova (BIBM, 2011)

Classification of Emerging Extreme Event Tracks in Multivariate Spatio-Temporal Physical Systems Using Dynamic Network Structures: Application to Hurricane Track Prediction. - Huseyin Sencan; Zhengzhang Chen; William Hendrix; Tatdow Pansombut; Fredrick H. M. Semazzi; Alok N. Choudhary; Vipin Kumar 001; Anatoli V. Melechko; Nagiza F. Samatova (IJCAI, 2011)

Efficient alpha, beta-motif Finder for Identification of Phenotype-related Functional Modules. - Matthew C. Schmidt; Andrea M. Rocha; Kanchana Padmanabhan; Zhengzhang Chen; Kathleen Scott; James R. Mihelcic; Nagiza F. Samatova (BMC Bioinform., 2011)

Hierarchical Classifier-Regression Ensemble for Multi-phase Non-linear Dynamic System Response Prediction: Application to Climate Analysis. - Doel L. Gonzalez; Zhengzhang Chen; Isaac K. Tetteh; Tatdow Pansombut; Fredrick H. M. Semazzi; Vipin Kumar 001; Anatoli V. Melechko; Nagiza F. Samatova (ICDM Workshops, 2012)

Spice: discovery of phenotype-determining component interplays. - Zhengzhang Chen; Kanchana Padmanabhan; Andrea M. Rocha; Yekaterina Shpanskaya; James R. Mihelcic; Kathleen Scott; Nagiza F. Samatova (BMC Syst. Biol., 2012)

Community-based anomaly detection in evolutionary networks. - Zhengzhang Chen; William Hendrix; Nagiza F. Samatova (J. Intell. Inf. Syst., 2012)

A probabilistic graphical model for brand reputation assessment in social networks. - Kunpeng Zhang 001; Doug Downey; Zhengzhang Chen; Yusheng Xie; Yu Cheng 001; Ankit Agrawal 001; Wei-keng Liao; Alok N. Choudhary (ASONAM, 2013)

Elver: Recommending Facebook pages in cold start situation without content features. - Yusheng Xie; Zhengzhang Chen; Kunpeng Zhang 001; Chen Jin; Yu Cheng 001; Ankit Agrawal 001; Alok N. Choudhary (IEEE BigData, 2013)

Feedback-driven multiclass active learning for data streams. - Yu Cheng 001; Zhengzhang Chen; Lu Liu 005; Jiang Wang; Ankit Agrawal 001; Alok N. Choudhary (CIKM, 2013)

Bootstrapping active name disambiguation with crowdsourcing. - Yu Cheng 001; Zhengzhang Chen; Jiang Wang; Ankit Agrawal 001; Alok N. Choudhary (CIKM, 2013)

Random walk-based graphical sampling in unbalanced heterogeneous bipartite social graphs. - Yusheng Xie; Zhengzhang Chen; Ankit Agrawal 001; Alok N. Choudhary; Lu Liu 005 (CIKM, 2013)

Forecast Oriented Classification of Spatio-Temporal Extreme Events. - Zhengzhang Chen; Yusheng Xie; Yu Cheng 001; Kunpeng Zhang 001; Ankit Agrawal 001; Wei-keng Liao; Nagiza F. Samatova; Alok N. Choudhary (IJCAI, 2013)

Detecting and Tracking Disease Outbreaks by Mining Social Media Data. - Yusheng Xie; Zhengzhang Chen; Alok N. Choudhary (IJCAI, 2013)

JobMiner: a real-time system for mining job-related patterns from social media. - Yu Cheng 001; Yusheng Xie; Zhengzhang Chen; Ankit Agrawal 001; Alok N. Choudhary; Songtao Guo (KDD, 2013)

Graphical Modeling of Macro Behavioral Targeting in Social Networks. - Ankit Agrawal 001; Zhengzhang Chen; Yu Cheng 001; Alok N. Choudhary; Haotian Liu; Md. Mostofa Ali Patwary; Yusheng Xie; Kunpeng Zhang 001 (SDM, 2013)

Automatic Detection and Correction of Multi-class Classification Errors Using System Whole-part Relationships. - Zhengzhang Chen; Alok N. Choudhary; John Jenkins; Vipin Kumar 001; Anatoli V. Melechko; Jinfeng Rao; Nagiza F. Samatova; Fredrick H. M. Semazzi (SDM, 2013)

Discovery of extreme events-related communities in contrasting groups of physical system networks. - Zhengzhang Chen; William Hendrix; Hang Guan; Isaac K. Tetteh; Alok N. Choudhary; Fredrick H. M. Semazzi; Nagiza F. Samatova (Data Min. Knowl. Discov., 2013)

Indexing bipartite memberships in web graphs. - Yusheng Xie; Zhengzhang Chen; Diana Palsetia; Ankit Agrawal 001; Alok N. Choudhary (ASONAM, 2014)

NUMARCK: Machine Learning Algorithm for Resiliency and Checkpointing. - Zhengzhang Chen; Seung Woo Son 001; William Hendrix; Ankit Agrawal 001; Wei-keng Liao; Alok N. Choudhary (SC, 2014)

Batch Mode Active Learning with Hierarchical-Structured Embedded Variance. - Yu Cheng 001; Zhengzhang Chen; Hongliang Fei; Fei Wang; Alok N. Choudhary (SDM, 2014)

MuSES: Multilingual Sentiment Elicitation System for Social Media Data. - Yusheng Xie; Zhengzhang Chen; Kunpeng Zhang 001; Yu Cheng 001; Daniel Honbo; Ankit Agrawal 001; Alok N. Choudhary (IEEE Intell. Syst., 2014)

Data Compression for the Exascale Computing Era - Survey. - Seung Woo Son 001; Zhengzhang Chen; William Hendrix; Ankit Agrawal 001; Wei-keng Liao; Alok N. Choudhary (Supercomput. Front. Innov., 2014)

Solving the maximum duo-preservation string mapping problem with linear programming. - Wenbin Chen 006; Zhengzhang Chen; Nagiza F. Samatova; Lingxi Peng; Jianxiong Wang; Maobin Tang (Theor. Comput. Sci., 2014)

A Scalable Hierarchical Clustering Algorithm Using Spark. - Chen Jin; Ruoqian Liu; Zhengzhang Chen; William Hendrix; Ankit Agrawal 001; Alok N. Choudhary (BigDataService, 2015)

Running MAP Inference on Million Node Graphical Models: A High Performance Computing Perspective. - Chen Jin; Qiang Fu 021; Huahua Wang; William Hendrix; Zhengzhang Chen; Ankit Agrawal 001; Arindam Banerjee 001; Alok N. Choudhary (CCGRID, 2015)

Pruned search: A machine learning based meta-heuristic approach for constrained continuous optimization. - Ruoqian Liu; Ankit Agrawal 001; Wei-keng Liao; Alok N. Choudhary; Zhengzhang Chen (IC3, 2015)

From Categorical to Numerical: Multiple Transitive Distance Learning and Embedding. - Kai Zhang 001; Qiaojun Wang; Zhengzhang Chen; Ivan Marsic; Vipin Kumar 001; Guofei Jiang; Jie Zhang 012 (SDM, 2015)

Incremental, distributed single-linkage hierarchical clustering algorithm using mapreduce. - Chen Jin; Zhengzhang Chen; William Hendrix; Ankit Agrawal 001; Alok N. Choudhary (SpringSim (HPS), 2015)

Entity Embedding-Based Anomaly Detection for Heterogeneous Categorical Events. - Ting Chen 007; Lu-An Tang; Yizhou Sun; Zhengzhang Chen; Kai Zhang 001 (IJCAI, 2016)

Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations. - Wei Cheng 002; Kai Zhang 001; Haifeng Chen; Guofei Jiang; Zhengzhang Chen; Wei Wang 010 (KDD, 2016)

Annealed Sparsity via Adaptive and Dynamic Shrinking. - Kai Zhang 001; Shandian Zhe; Chaoran Cheng; Zhi Wei 001; Zhengzhang Chen; Haifeng Chen; Guofei Jiang; Yuan Qi 001; Jieping Ye (KDD, 2016)

Integrating Community and Role Detection in Information Networks. - Ting Chen 007; Lu-An Tang; Yizhou Sun; Zhengzhang Chen; Haifeng Chen; Guofei Jiang (SDM, 2016)

GID: Graph-based Intrusion Detection on Massive Process Traces for Enterprise Security Systems. - Boxiang Dong; Zhengzhang Chen; Hui Wang 013; Lu-An Tang; Kai Zhang 001; Ying Lin; Haifeng Chen; Guofei Jiang (CoRR, 2016)

Enhancing semi-supervised learning through label-aware base kernels. - Qiaojun Wang; Kai Zhang 001; Zhengzhang Chen; Dequan Wang; Guofei Jiang; Ivan Marsic (Neurocomputing, 2016)

Distinguish Polarity in Bag-of-Words Visualization. - Yusheng Xie; Zhengzhang Chen; Ankit Agrawal 001; Alok N. Choudhary (AAAI, 2017)

Efficient Discovery of Abnormal Event Sequences in Enterprise Security Systems. - Boxiang Dong; Zhengzhang Chen; Wendy Hui Wang; Lu-An Tang; Kai Zhang 001; Ying Lin; Zhichun Li; Haifeng Chen (CIKM, 2017)

Accelerating Dependency Graph Learning from Heterogeneous Categorical Event Streams via Knowledge Transfer. - Chen Luo 001; Zhengzhang Chen; Lu-An Tang; Anshumali Shrivastava; Zhichun Li (CoRR, 2017)

SILVERBACK+: scalable association mining via fast list intersection for columnar social data. - Yusheng Xie; Zhengzhang Chen; Diana Palsetia; Goce Trajcevski; Ankit Agrawal 001; Alok N. Choudhary (Knowl. Inf. Syst., 2017)

Behavior-based Community Detection: Application to Host Assessment In Enterprise Information Networks. - Cheng Cao; Zhengzhang Chen; James Caverlee; Lu-An Tang; Chen Luo 001; Zhichun Li (CIKM, 2018)

Collaborative Alert Ranking for Anomaly Detection. - Ying Lin; Zhengzhang Chen; Cheng Cao; Lu-An Tang; Kai Zhang 001; Wei Cheng 002; Zhichun Li (CIKM, 2018)

TINET: Learning Invariant Networks via Knowledge Transfer. - Chen Luo 001; Zhengzhang Chen; Lu-An Tang; Anshumali Shrivastava; Zhichun Li; Haifeng Chen; Jieping Ye (KDD, 2018)

Deep Program Reidentification: A Graph Neural Network Solution. - Shen Wang 005; Zhengzhang Chen; Ding Li 001; Lu-An Tang; Jingchao Ni; Zhichun Li; Junghwan Rhee; Haifeng Chen; Philip S. Yu (CoRR, 2018)

Heterogeneous Graph Matching Networks for Unknown Malware Detection. - Shen Wang 005; Zhengzhang Chen; Xiao Yu 007; Ding Li 001; Jingchao Ni; Lu-An Tang; Jiaping Gui; Zhichun Li; Haifeng Chen; Philip S. Yu (IJCAI, 2019)

NoDoze: Combatting Threat Alert Fatigue with Automated Provenance Triage. - Wajih Ul Hassan; Shengjian Guo; Ding Li 001; Zhengzhang Chen; Kangkook Jee; Zhichun Li; Adam Bates 001 (NDSS, 2019)

Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification. - Shen Wang 005; Zhengzhang Chen; Ding Li 001; Zhichun Li; Lu-An Tang; Jingchao Ni; Junghwan Rhee; Haifeng Chen; Philip S. Yu (SDM, 2019)

Adversarial Defense Framework for Graph Neural Network. - Shen Wang 005; Zhengzhang Chen; Jingchao Ni; Xiao Yu 007; Zhichun Li; Haifeng Chen; Philip S. Yu (CoRR, 2019)

Heterogeneous Graph Matching Networks. - Shen Wang 005; Zhengzhang Chen; Xiao Yu 007; Ding Li 001; Jingchao Ni; Lu-An Tang; Jiaping Gui; Zhichun Li; Haifeng Chen; Philip S. Yu (CoRR, 2019)

Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation. - Xin Dong 010; Jingchao Ni; Wei Cheng 002; Zhengzhang Chen; Bo Zong; Dongjin Song; Yanchi Liu; Haifeng Chen; Gerard de Melo (AAAI, 2020)

This is Why We Can't Cache Nice Things: Lightning-Fast Threat Hunting using Suspicion-Based Hierarchical Storage. - Wajih Ul Hassan; Ding Li 001; Kangkook Jee; Xiao Yu 007; Kexuan Zou; Dawei Wang; Zhengzhang Chen; Zhichun Li; Junghwan Rhee; Jiaping Gui; Adam Bates 001 (ACSAC, 2020)

APTrace: A Responsive System for Agile Enterprise Level Causality Analysis. - Jiaping Gui; Ding Li 001; Zhengzhang Chen; Junghwan Rhee; Xusheng Xiao; Mu Zhang 001; Kangkook Jee; Zhichun Li; Haifeng Chen (ICDE, 2020)

T2-Net: A Semi-supervised Deep Model for Turbulence Forecasting. - Denghui Zhang; Yanchi Liu; Wei Cheng 002; Bo Zong; Jingchao Ni; Zhengzhang Chen; Haifeng Chen; Hui Xiong 001 (ICDM, 2020)

You Are What You Do: Hunting Stealthy Malware via Data Provenance Analysis. - Qi Wang 017; Wajih Ul Hassan; Ding Li 001; Kangkook Jee; Xiao Yu 007; Kexuan Zou; Junghwan Rhee; Zhengzhang Chen; Wei Cheng 002; Carl A. Gunter; Haifeng Chen (NDSS, 2020)

Anomaly Detection on Web-User Behaviors Through Deep Learning. - Jiaping Gui; Zhengzhang Chen; Xiao Yu 007; Cristian Lumezanu; Haifeng Chen (SecureComm (1), 2020)

A Generic Edge-Empowered Graph Convolutional Network via Node-Edge Mutual Enhancement. - Pengyang Wang; Jiaping Gui; Zhengzhang Chen; Junghwan Rhee; Haifeng Chen; Yanjie Fu (WWW, 2020)

AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning. - Yuening Li; Zhengzhang Chen; Daochen Zha; Kaixiong Zhou; Haifeng Jin; Haifeng Chen; Xia Hu 001 (CoRR, 2020)

Introduction to the Special Issue on Retrieving and Learning from Internet of Things Data. - Haibo Hu; Rik Sarkar; Zhengzhang Chen (Trans. Data Sci., 2020)

Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series. - Yinjun Wu; Jingchao Ni; Wei Cheng 002; Bo Zong; Dongjin Song; Zhengzhang Chen; Yanchi Liu; Xuchao Zhang; Haifeng Chen; Susan B. Davidson (AAAI, 2021)

Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs. - Lei Cai; Zhengzhang Chen; Chen Luo 003; Jiaping Gui; Jingchao Ni; Ding Li 001; Haifeng Chen (CIKM, 2021)

Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization. - Jingchao Ni; Zhengzhang Chen; Wei Cheng 002; Bo Zong; Dongjin Song; Yanchi Liu; Xuchao Zhang; Haifeng Chen (CIKM, 2021)

FaceSec: A Fine-Grained Robustness Evaluation Framework for Face Recognition Systems. - Liang Tong; Zhengzhang Chen; Jingchao Ni; Wei Cheng 002; Dongjin Song; Haifeng Chen; Yevgeniy Vorobeychik (CVPR, 2021)

AutoOD: Neural Architecture Search for Outlier Detection. - Yuening Li; Zhengzhang Chen; Daochen Zha; Kaixiong Zhou; Haifeng Jin; Haifeng Chen; Xia Hu 001 (ICDE, 2021)

Privacy-Preserving Fair Machine Learning Without Collecting Sensitive Demographic Data. - Hui Hu; Mike Borowczak; Zhengzhang Chen (IJCNN, 2021)

Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection. - Zhiwei Wang 001; Zhengzhang Chen; Jingchao Ni; Hui Liu 031; Haifeng Chen; Jiliang Tang (KDD, 2021)

Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection. - Xinyang Feng; Dongjin Song; Yuncong Chen; Zhengzhang Chen; Jingchao Ni; Haifeng Chen (ACM Multimedia, 2021)

Unsupervised Document Embedding via Contrastive Augmentation. - Dongsheng Luo; Wei Cheng 002; Jingchao Ni; Wenchao Yu; Xuchao Zhang; Bo Zong; Yanchi Liu; Zhengzhang Chen; Dongjin Song; Haifeng Chen; Xiang Zhang 001 (CoRR, 2021)

Learning Disentangled Representations for Time Series. - Yuening Li; Zhengzhang Chen; Daochen Zha; Mengnan Du; Denghui Zhang; Haifeng Chen; Xia Hu 001 (CoRR, 2021)

Anomalous Event Sequence Detection. - Boxiang Dong; Zhengzhang Chen; Lu-An Tang; Haifeng Chen; Hui Wang 013; Kai Zhang 001; Ying Lin; Zhichun Li (IEEE Intell. Syst., 2021)

Towards Robust Graph Neural Networks via Adversarial Contrastive Learning. - Shen Wang 005; Zhengzhang Chen; Jingchao Ni; Haifeng Chen; Philip S. Yu (IEEE Big Data, 2022)

Superclass-Conditional Gaussian Mixture Model For Learning Fine-Grained Embeddings. - Jingchao Ni; Wei Cheng 002; Zhengzhang Chen; Takayoshi Asakura; Tomoya Soma; Sho Kato; Haifeng Chen (ICLR, 2022)

Towards Learning Disentangled Representations for Time Series. - Yuening Li; Zhengzhang Chen; Daochen Zha; Mengnan Du; Jingchao Ni; Denghui Zhang; Haifeng Chen; Xia Hu 001 (KDD, 2022)

Multi-source Inductive Knowledge Graph Transfer. - Junheng Hao; Lu-An Tang; Yizhou Sun; Zhengzhang Chen; Haifeng Chen; Junghwan Rhee; Zhichuan Li; Wei Wang 010 (ECML/PKDD (2), 2022)

Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning. - Yuening Li; Zhengzhang Chen; Daochen Zha; Kaixiong Zhou; Haifeng Jin; Haifeng Chen; Xia Hu 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

GLAD: Content-Aware Dynamic Graphs For Log Anomaly Detection. - Yufei Li 001; Yanchi Liu; Haoyu Wang; Zhengzhang Chen; Wei Cheng 002; Yuncong Chen; Wenchao Yu; Haifeng Chen; Cong Liu 005 (ICKG, 2023)

Incremental Causal Graph Learning for Online Root Cause Analysis. - Dongjie Wang; Zhengzhang Chen; Yanjie Fu; Yanchi Liu; Haifeng Chen (KDD, 2023)

Interdependent Causal Networks for Root Cause Localization. - Dongjie Wang; Zhengzhang Chen; Jingchao Ni; Liang Tong; Zheng Wang; Yanjie Fu; Haifeng Chen (KDD, 2023)

Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning. - Yizhou Zhang; Jingchao Ni; Wei Cheng 002; Zhengzhang Chen; Liang Tong; Haifeng Chen; Yan Liu 002 (NeurIPS, 2023)

Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization. - Dongjie Wang; Zhengzhang Chen; Jingchao Ni; Liang Tong; Zheng Wang; Yanjie Fu; Haifeng Chen (CoRR, 2023)

Disentangled Causal Graph Learning for Online Unsupervised Root Cause Analysis. - Dongjie Wang; Zhengzhang Chen; Yanjie Fu; Yanchi Liu; Haifeng Chen (CoRR, 2023)

Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models. - Chen Ling 003; Xujiang Zhao; Jiaying Lu 001; Chengyuan Deng; Can Zheng; Junxiang Wang; Tanmoy Chowdhury; Yun Li 005; Hejie Cui; Xuchao Zhang; Tianjiao Zhao; Amit Panalkar; et al. (CoRR, 2023)

Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty. - Chen Ling 003; Xujiang Zhao; Xuchao Zhang; Yanchi Liu; Wei Cheng 002; Haoyu Wang; Zhengzhang Chen; Takao Osaki; Katsushi Matsuda; Haifeng Chen; Liang Zhao 002 (CoRR, 2023)

Prompt-based Domain Discrimination for Multi-source Time Series Domain Adaptation. - Junxiang Wang; Guangji Bai; Wei Cheng 002; Zhengzhang Chen; Liang Zhao 002; Haifeng Chen (CoRR, 2023)

POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning. - Junxiang Wang; Guangji Bai; Wei Cheng 002; Zhengzhang Chen; Liang Zhao 002; Haifeng Chen (KDD, 2024)

MULAN: Multi-modal Causal Structure Learning and Root Cause Analysis for Microservice Systems. - Lecheng Zheng; Zhengzhang Chen; Jingrui He; Haifeng Chen (WWW, 2024)

Multi-modal Causal Structure Learning and Root Cause Analysis. - Lecheng Zheng; Zhengzhang Chen; Jingrui He; Haifeng Chen (CoRR, 2024)

LEMMA-RCA: A Large Multi-modal Multi-domain Dataset for Root Cause Analysis. - Lecheng Zheng; Zhengzhang Chen; Dongjie Wang; Chengyuan Deng; Reon Matsuoka; Haifeng Chen (CoRR, 2024)

RIO-CPD: A Riemannian Geometric Method for Correlation-aware Online Change Point Detection. - Chengyuan Deng; Zhengzhang Chen; Xujiang Zhao; Haoyu Wang; Junxiang Wang; Haifeng Chen; Jie Gao (CoRR, 2024)

Online Multi-modal Root Cause Analysis. - Lecheng Zheng; Zhengzhang Chen; Haifeng Chen; Jingrui He (CoRR, 2024)

Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation. - Minhua Lin; Zhengzhang Chen; Yanchi Liu; Xujiang Zhao; Zongyu Wu 001; Junxiang Wang; Xiang Zhang 001; Suhang Wang; Haifeng Chen (CoRR, 2024)

Exploring Multi-Modal Integration with Tool-Augmented LLM Agents for Precise Causal Discovery. - ChengAo Shen; Zhengzhang Chen; Dongsheng Luo; Dongkuan Xu; Haifeng Chen; Jingchao Ni (CoRR, 2024)

Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery. - ChengAo Shen; Zhengzhang Chen; Dongsheng Luo; Dongkuan Xu; Haifeng Chen; Jingchao Ni (ACL (Findings), 2025)

MixLLM: Dynamic Routing in Mixed Large Language Models. - Xinyuan Wang 011; Yanchi Liu; Wei Cheng 002; Xujiang Zhao; Zhengzhang Chen; Wenchao Yu; Yanjie Fu; Haifeng Chen (NAACL (Long Papers), 2025)

Evidence-Based Out-of-Distribution Detection on Multi-Label Graphs. - Ruomeng Ding; Xujiang Zhao; Chen Zhao 010; Minglai Shao 001; Zhengzhang Chen; Haifeng Chen (SDM, 2025)

Iterative Feature Space Optimization through Incremental Adaptive Evaluation. - Yanping Wu; Yanyong Huang; Zhengzhang Chen; Zijun Yao 001; Yanjie Fu; Kunpeng Liu 001; Xiao Luo 001; Dongjie Wang (CoRR, 2025)

Resolving Editing-Unlearning Conflicts: A Knowledge Codebook Framework for Large Language Model Updating. - Binchi Zhang; Zhengzhang Chen; Zaiyi Zheng; Jundong Li; Haifeng Chen (CoRR, 2025)

Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion. - Binchi Zhang; Zaiyi Zheng; Zhengzhang Chen; Jundong Li (CoRR, 2025)