Storytelling in heterogeneous Twitter entity network based on hierarchical cluster routing. - Xuchao Zhang; Zhiqian Chen; Weisheng Zhong; Arnold P. Boedihardjo; Chang-Tien Lu (IEEE BigData, 2016)

Automatical Storyline Generation with Help from Twitter. - Ting Hua; Xuchao Zhang; Wei Wang 064; Chang-Tien Lu; Naren Ramakrishnan (CIKM, 2016)

TRACES: Generating Twitter stories via shared subspace and temporal smoothness. - Xuchao Zhang; Zhiqian Chen; Liang Zhao 002; Arnold P. Boedihardjo; Chang-Tien Lu (IEEE BigData, 2017)

Trendi: Tracking stories in news and microblogs via emerging, evolving and fading topics. - Xuchao Zhang; Liang Zhao 002; Zhiqian Chen; Arnold P. Boedihardjo; Jing Dai; Chang-Tien Lu (IEEE BigData, 2017)

Spatiotemporal Event Forecasting from Incomplete Hyper-local Price Data. - Xuchao Zhang; Liang Zhao 002; Arnold P. Boedihardjo; Chang-Tien Lu; Naren Ramakrishnan (CIKM, 2017)

Online and Distributed Robust Regressions Under Adversarial Data Corruption. - Xuchao Zhang; Liang Zhao 002; Arnold P. Boedihardjo; Chang-Tien Lu (ICDM, 2017)

Multimodal Storytelling via Generative Adversarial Imitation Learning. - Zhiqian Chen; Xuchao Zhang; Arnold P. Boedihardjo; Jing Dai; Chang-Tien Lu (IJCAI, 2017)

Robust Regression via Heuristic Hard Thresholding. - Xuchao Zhang; Liang Zhao 002; Arnold P. Boedihardjo; Chang-Tien Lu (IJCAI, 2017)

Situation-Based Interpretable Learning for Personality Prediction in Social Media. - Lei Zhang 158; Liang Zhao 002; Xuchao Zhang; Wenmo Kong; Zitong Sheng; Chang-Tien Lu (IEEE BigData, 2018)

Rational Neural Networks for Approximating Graph Convolution Operator on Jump Discontinuities. - Zhiqian Chen; Feng Chen 001; Rongjie Lai; Xuchao Zhang; Chang-Tien Lu (ICDM, 2018)

Robust Regression via Online Feature Selection Under Adversarial Data Corruption. - Xuchao Zhang; Shuo Lei; Liang Zhao 002; Arnold P. Boedihardjo; Chang-Tien Lu (ICDM, 2018)

Distributed Self-Paced Learning in Alternating Direction Method of Multipliers. - Xuchao Zhang; Liang Zhao 002; Zhiqian Chen; Chang-Tien Lu (IJCAI, 2018)

Water Disaggregation via Shape Features based Bayesian Discriminative Sparse Coding. - Bingsheng Wang; Xuchao Zhang; Chang-Tien Lu; Feng Chen 001 (CoRR, 2018)

Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator. - Zhiqian Chen; Feng Chen 001; Rongjie Lai; Xuchao Zhang; Chang-Tien Lu (CoRR, 2018)

Feature driven learning framework for cybersecurity event detection. - Taoran Ji; Xuchao Zhang; Nathan Self; Kaiqun Fu; Chang-Tien Lu; Naren Ramakrishnan (ASONAM, 2019)

Similarity-Aware Network Embedding with Self-Paced Learning. - Chao Huang 001; Baoxu Shi; Xuchao Zhang; Xian Wu 003; Nitesh V. Chawla (CIKM, 2019)

Deep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity. - Chao Huang 001; Xian Wu 003; Xuchao Zhang; Suwen Lin; Nitesh V. Chawla (CIKM, 2019)

Modeling the Relationship between User Comments and Edits in Document Revision. - Xuchao Zhang; Dheeraj Rajagopal; Michael Gamon; Sujay Kumar Jauhar; Chang-Tien Lu (EMNLP/IJCNLP (1), 2019)

Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics. - Chao Huang 001; Xian Wu 003; Xuchao Zhang; Chuxu Zhang; Jiashu Zhao; Dawei Yin; Nitesh V. Chawla (KDD, 2019)

Mitigating Uncertainty in Document Classification. - Xuchao Zhang; Fanglan Chen; Chang-Tien Lu; Naren Ramakrishnan (NAACL-HLT (1), 2019)

Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation. - Xuchao Zhang; Shuo Lei; Liang Zhao 002; Arnold P. Boedihardjo; Chang-Tien Lu (ACM Trans. Knowl. Discov. Data, 2019)

Scalable Robust Models Under Adversarial Data Corruption. - Xuchao Zhang (2019)

TapNet: Multivariate Time Series Classification with Attentional Prototypical Network. - Xuchao Zhang; Yifeng Gao; Jessica Lin 001; Chang-Tien Lu (AAAI, 2020)

Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data. - Xuchao Zhang; Xian Wu; Fanglan Chen; Liang Zhao 002; Chang-Tien Lu (AAAI, 2020)

Towards More Accurate Uncertainty Estimation In Text Classification. - Jianfeng He; Xuchao Zhang; Shuo Lei; Zhiqian Chen; Fanglan Chen; Abdulaziz Alhamadani; Bei Xiao; Chang-Tien Lu (EMNLP (1), 2020)

Robust Multi-Target Regression for Correlated Data Corruption. - Xuchao Zhang; Yingwen Shao (ICDM, 2020)

Temporal Context-Aware Representation Learning for Question Routing. - Xuchao Zhang; Wei Cheng 002; Bo Zong; Yuncong Chen; Jianwu Xu; Ding Li 001; Haifeng Chen (WSDM, 2020)

A Concept-based Abstraction-Aggregation Deep Neural Network for Interpretable Document Classification. - Tian Shi; Xuchao Zhang; Ping Wang 024; Chandan K. Reddy (CoRR, 2020)

Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations. - Shuo Lei; Xuchao Zhang; Jianfeng He; Fanglan Chen; Chang-Tien Lu (CoRR, 2020)

Semantic Editing On Segmentation Map Via Multi-Expansion Loss. - Jianfeng He; Xuchao Zhang; Shuo Lei; Shuhui Wang; Qingming Huang; Chang-Tien Lu; Bei Xiao (CoRR, 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)

Multi-Task Recurrent Modular Networks. - Dongkuan Xu; Wei Cheng 002; Xin Dong 010; Bo Zong; Wenchao Yu; Jingchao Ni; Dongjin Song; Xuchao Zhang; Haifeng Chen; Xiang Zhang 001 (AAAI, 2021)

Predicting Hepatoma-Related Genes Based on Representation Learning of PPI network and Gene Ontology Annotations. - Tao Wang 082; Zhiyuan Shao; Yifu Xiao; Xuchao Zhang; Yitian Chen; Binze Shi; Siyu Chen; Yuxian Wang; Jiajie Peng; Xuequn Shang 001 (BIBM, 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)

Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation. - Liyan Xu; Xuchao Zhang; Xujiang Zhao; Haifeng Chen; Feng Chen 001; Jinho D. Choi (EMNLP (1), 2021)

Reducing Noise Pixels and Metric Bias in Semantic Inpainting on Segmentation Map. - Jianfeng He; Bei Xiao; Xuchao Zhang; Shuo Lei; Shuhui Wang; Chang-Tien Lu (ICCVW, 2021)

Aspect-based Sentiment Classification via Reinforcement Learning. - Lichen Wang; Bo Zong; Yunyu Liu; Can Qin; Wei Cheng 002; Wenchao Yu; Xuchao Zhang; Haifeng Chen; Yun Fu 001 (ICDM, 2021)

Few-Shot Semantic Segmentation via Prototype Augmentation with Image-Level Annotations. - Shuo Lei; Xuchao Zhang; Jianfeng He; Fanglan Chen; Chang-Tien Lu (ICME, 2021)

Unsupervised Concept Representation Learning for Length-Varying Text Similarity. - Xuchao Zhang; Bo Zong; Wei Cheng 002; Jingchao Ni; Yanchi Liu; Haifeng Chen (NAACL-HLT, 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)

Do Multi-Lingual Pre-trained Language Models Reveal Consistent Token Attributions in Different Languages? - Junxiang Wang; Xuchao Zhang; Bo Zong; Yanchi Liu; Wei Cheng 002; Jingchao Ni; Haifeng Chen; Liang Zhao 002 (CoRR, 2021)

Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency Graph. - Liyan Xu; Xuchao Zhang; Bo Zong; Yanchi Liu; Wei Cheng 002; Jingchao Ni; Haifeng Chen; Liang Zhao 002; Jinho D. Choi (AAAI, 2022)

Cross-Domain Few-Shot Semantic Segmentation. - Shuo Lei; Xuchao Zhang; Jianfeng He; Fanglan Chen; Bowen Du 001; Chang-Tien Lu (ECCV (30), 2022)

Seed: Sound Event Early Detection Via Evidential Uncertainty. - Xujiang Zhao; Xuchao Zhang; Wei Cheng 002; Wenchao Yu; Yuncong Chen; Haifeng Chen; Feng Chen 001 (ICASSP, 2022)

DeepGAR: Deep Graph Learning for Analogical Reasoning. - Chen Ling 003; Tanmoy Chowdhury; Junji Jiang; Junxiang Wang; Xuchao Zhang; Haifeng Chen; Liang Zhao 002 (ICDM, 2022)

CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event Sequences. - Shengming Zhang; Yanchi Liu; Xuchao Zhang; Wei Cheng 002; Haifeng Chen; Hui Xiong 001 (KDD, 2022)

One Document, Many Revisions: A Dataset for Classification and Description of Edit Intents. - Dheeraj Rajagopal; Xuchao Zhang; Michael Gamon; Sujay Kumar Jauhar; Diyi Yang; Eduard H. Hovy (LREC, 2022)

Uncertainty-Aware Cross-Lingual Transfer with Pseudo Partial Labels. - Shuo Lei; Xuchao Zhang; Jianfeng He; Fanglan Chen; Chang-Tien Lu (NAACL-HLT (Findings), 2022)

LANS: Large-scale Arabic News Summarization Corpus. - Abdulaziz Alhamadani; Xuchao Zhang; Jianfeng He; Chang-Tien Lu (CoRR, 2022)

Semantic inpainting on segmentation map via multi-expansion loss. - Jianfeng He; Xuchao Zhang; Shuo Lei; Shuhui Wang; Chang-Tien Lu; Bei Xiao (Neurocomputing, 2022)

Online and Distributed Robust Regressions with Extremely Noisy Labels. - Shuo Lei; Xuchao Zhang; Liang Zhao 002; Arnold P. Boedihardjo; Chang-Tien Lu (ACM Trans. Knowl. Discov. Data, 2022)

Corpus-level and Concept-based Explanations for Interpretable Document Classification. - Tian Shi; Xuchao Zhang; Ping Wang 024; Chandan K. Reddy (ACM Trans. Knowl. Discov. Data, 2022)

Time Series Contrastive Learning with Information-Aware Augmentations. - Dongsheng Luo; Wei Cheng 002; Yingheng Wang; Dongkuan Xu; Jingchao Ni; Wenchao Yu; Xuchao Zhang; Yanchi Liu; Yuncong Chen; Haifeng Chen; Xiang Zhang 001 (AAAI, 2023)

TART: Improved Few-shot Text Classification Using Task-Adaptive Reference Transformation. - Shuo Lei; Xuchao Zhang; Jianfeng He; Fanglan Chen; Chang-Tien Lu (ACL (1), 2023)

Open-ended Commonsense Reasoning with Unrestricted Answer Candidates. - Chen Ling 003; Xuchao Zhang; Xujiang Zhao; Yanchi Liu; Wei Cheng 002; Mika Oishi; Takao Osaki; Katsushi Matsuda; Haifeng Chen; Liang Zhao 002 (EMNLP (Findings), 2023)

Multi-Label Temporal Evidential Neural Networks for Early Event Detection. - Xujiang Zhao; Xuchao Zhang; Chen Zhao 010; Jin-Hee Cho; Lance M. Kaplan; Dong Hyun Jeong; Audun Jøsang; Haifeng Chen; Feng Chen 001 (ICASSP, 2023)

Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models. - Toufique Ahmed; Supriyo Ghosh; Chetan Bansal; Thomas Zimmermann 001; Xuchao Zhang; Saravan Rajmohan (ICSE, 2023)

CLUR: Uncertainty Estimation for Few-Shot Text Classification with Contrastive Learning. - Jianfeng He; Xuchao Zhang; Shuo Lei; Abdulaziz Alhamadani; Fanglan Chen; Bei Xiao; Chang-Tien Lu (KDD, 2023)

AutoARTS: Taxonomy, Insights and Tools for Root Cause Labelling of Incidents in Microsoft Azure. - Pradeep Dogga; Chetan Bansal; Richard Costleigh; Gopinath Jayagopal; Suman Nath; Xuchao Zhang (USENIX ATC, 2023)

LANS: Large-scale Arabic News Summarization Corpus. - Abdulaziz Alhamadani; Xuchao Zhang; Jianfeng He; Aadyant Khatri; Chang-Tien Lu (ArabicNLP, 2023)

Knowledge-enhanced Neural Machine Reasoning: A Review. - Tanmoy Chowdhury; Chen Ling 003; Xuchao Zhang; Xujiang Zhao; Guangji Bai; Jian Pei 001; Haifeng Chen; Liang Zhao 002 (CoRR, 2023)

Empowering Practical Root Cause Analysis by Large Language Models for Cloud Incidents. - Yinfang Chen; Huaibing Xie; Minghua Ma; Yu Kang 006; Xin Gao; Liu Shi; Yunjie Cao; Xuedong Gao; Hao Fan; Ming Wen 001; Jun Zeng 006; Supriyo Ghosh; et al. (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)

Hybrid Retrieval-Augmented Generation for Real-time Composition Assistance. - Xuchao Zhang; Menglin Xia; Camille Couturier; Guoqing Zheng; Saravan Rajmohan; Victor Rühle (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)

PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis. - Dylan Zhang; Xuchao Zhang; Chetan Bansal; Pedro Henrique B. Las-Casas; Rodrigo Fonseca; Saravan Rajmohan (CoRR, 2023)

Open-ended Commonsense Reasoning with Unrestricted Answer Scope. - Chen Ling 003; Xuchao Zhang; Xujiang Zhao; Yanchi Liu; Wei Cheng 002; Mika Oishi; Takao Osaki; Katsushi Matsuda; Haifeng Chen; Liang Zhao 002 (CoRR, 2023)

Building AI Agents for Autonomous Clouds: Challenges and Design Principles. - Manish Shetty; Yinfang Chen; Gagan Somashekar; Minghua Ma; Yogesh Simmhan; Xuchao Zhang; Jonathan Mace; Dax Vandevoorde; Pedro Henrique B. Las-Casas; Shachee Mishra Gupta; Suman Nath; Chetan Bansal; et al. (SoCC, 2024)

Hybrid-RACA: Hybrid Retrieval-Augmented Composition Assistance for Real-time Text Prediction. - Menglin Xia; Xuchao Zhang; Camille Couturier; Guoqing Zheng; Saravan Rajmohan; Victor Rühle (EMNLP (Industry Track), 2024)

Automatic Root Cause Analysis via Large Language Models for Cloud Incidents. - Yinfang Chen; Huaibing Xie; Minghua Ma; Yu Kang 006; Xin Gao; Liu Shi; Yunjie Cao; Xuedong Gao; Hao Fan; Ming Wen 001; Jun Zeng 006; Supriyo Ghosh; et al. (EuroSys, 2024)

Uncertainty Quantification for In-Context Learning of Large Language Models. - Chen Ling 003; Xujiang Zhao; Xuchao Zhang; Wei Cheng 002; Yanchi Liu; Yiyou Sun; Mika Oishi; Takao Osaki; Katsushi Matsuda; Jie Ji; Guangji Bai; Liang Zhao 002; et al. (NAACL-HLT, 2024)

CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models. - Peng Xia 005; Ze Chen; Juanxi Tian; Yangrui Gong; Ruibo Hou; Yue Xu; Zhenbang Wu; Zhiyuan Fan; Yiyang Zhou; Kangyu Zhu; Wenhao Zheng; Zhaoyang Wang 004; et al. (NeurIPS, 2024)

X-Lifecycle Learning for Cloud Incident Management using LLMs. - Drishti Goel; Fiza Husain; Aditya Singh; Supriyo Ghosh; Anjaly Parayil; Chetan Bansal; Xuchao Zhang; Saravan Rajmohan (SIGSOFT FSE Companion, 2024)

Exploring LLM-Based Agents for Root Cause Analysis. - Devjeet Roy; Xuchao Zhang; Rashi Bhave; Chetan Bansal; Pedro Henrique B. Las-Casas; Rodrigo Fonseca; Saravan Rajmohan (SIGSOFT FSE Companion, 2024)

Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4. - Xuchao Zhang; Supriyo Ghosh; Chetan Bansal; Rujia Wang; Minghua Ma; Yu Kang 006; Saravan Rajmohan (SIGSOFT FSE Companion, 2024)

LM-PACE: Confidence Estimation by Large Language Models for Effective Root Causing of Cloud Incidents. - Dylan Zhang; Xuchao Zhang; Chetan Bansal; Pedro Henrique B. Las-Casas; Rodrigo Fonseca; Saravan Rajmohan (SIGSOFT FSE Companion, 2024)

Uncertainty Decomposition and Quantification for In-Context Learning of Large Language Models. - Chen Ling 003; Xujiang Zhao; Wei Cheng 002; Yanchi Liu; Yiyou Sun; Xuchao Zhang; Mika Oishi; Takao Osaki; Katsushi Matsuda; Jie Ji; Guangji Bai; Liang Zhao 002; et al. (CoRR, 2024)

Unveiling Context-Aware Criteria in Self-Assessing LLMs. - Taneesh Gupta; Shivam Shandilya; Xuchao Zhang; Supriyo Ghosh; Chetan Bansal; Huaxiu Yao; Saravan Rajmohan (CoRR, 2024)

SWEPO: Simultaneous Weighted Preference Optimization for Group Contrastive Alignment. - Taneesh Gupta; Rahul Madhavan; Xuchao Zhang; Chetan Bansal; Saravan Rajmohan (CoRR, 2024)

REFA: Reference Free Alignment for multi-preference optimization. - Taneesh Gupta; Rahul Madhavan; Xuchao Zhang; Chetan Bansal; Saravan Rajmohan (CoRR, 2024)

CARMO: Dynamic Criteria Generation for Context Aware Reward Modelling. - Taneesh Gupta; Shivam Shandilya; Xuchao Zhang; Rahul Madhavan; Supriyo Ghosh; Chetan Bansal; Huaxiu Yao; Saravan Rajmohan (ACL (Findings), 2025)

Synergistic Weak-Strong Collaboration by Aligning Preferences. - Yizhu Jiao; Xuchao Zhang; Zhaoyang Wang 004; Yubo Ma; Zhun Deng; Rujia Wang; Chetan Bansal; Saravan Rajmohan; Jiawei Han 001; Huaxiu Yao (ACL (1), 2025)

CREAM: Consistency Regularized Self-Rewarding Language Models. - Zhaoyang Wang 004; Weilei He; Zhiyuan Liang; Xuchao Zhang; Chetan Bansal; Ying Wei; Weitong Zhang; Huaxiu Yao (ICLR, 2025)

Anyprefer: An Agentic Framework for Preference Data Synthesis. - Yiyang Zhou; Zhaoyang Wang 004; Tianle Wang 009; Shangyu Xing; Peng Xia 005; Bo Li; Kaiyuan Zheng; Zijian Zhang 010; Zhaorun Chen; Wenhao Zheng; Xuchao Zhang; Chetan Bansal; et al. (ICLR, 2025)

Verifiable Format Control for Large Language Model Generations. - Zhaoyang Wang 004; Jinqi Jiang; Huichi Zhou; Wenhao Zheng; Xuchao Zhang; Chetan Bansal; Huaxiu Yao (NAACL (Findings), 2025)

cfMethylPre: deep transfer learning enhances cancer detection based on circulating cell-free DNA methylation profiling. - Xuchao Zhang; Jing Chen; Yongtian Wang; Xiaofeng Wang; Jialu Hu; Jiajie Peng; Xuequn Shang 001; Yanpu Wang; Tao Wang 082 (Briefings Bioinform., 2025)

AMPO: Active Multi-Preference Optimization. - Taneesh Gupta; Rahul Madhavan; Xuchao Zhang; Chetan Bansal; Saravan Rajmohan (CoRR, 2025)

eARCO: Efficient Automated Root Cause Analysis with Prompt Optimization. - Drishti Goel; Raghav Magazine; Supriyo Ghosh; Akshay Nambi 001; Prathamesh Deshpande; Xuchao Zhang; Chetan Bansal; Saravan Rajmohan (CoRR, 2025)

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search. - Dongge Han; Menglin Xia; Daniel Madrigal Diaz; Samuel Kessler; Ankur Mallick; Xuchao Zhang; Mirian del Carmen Hipolito Garcia; Jin Xu; Victor Rühle; Saravan Rajmohan (CoRR, 2025)