Xuchao Zhang

According to our database, Xuchao Zhang authored at least 70 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

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

CoRR, 2024

Uncertainty Decomposition and Quantification for In-Context Learning of Large Language Models.

Chen Ling, Xujiang Zhao, Wei Cheng, Yanchi Liu, Yiyou Sun, Xuchao Zhang, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen

CoRR, 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, Saravan Rajmohan

CoRR, 2024

Automatic Root Cause Analysis via Large Language Models for Cloud Incidents.

Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xuedong Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo Ghosh, Xuchao Zhang, Chaoyun Zhang, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang, Tianyin Xu

Proceedings of the Nineteenth European Conference on Computer Systems, 2024

2023

Open-ended Commonsense Reasoning with Unrestricted Answer Scope.

Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao

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

Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty.

Chen Ling, Xujiang Zhao, Xuchao Zhang, Yanchi Liu, Wei Cheng, Haoyu Wang, Zhengzhang Chen, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao

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

Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models.

Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Carl Yang, Liang Zhao

CoRR, 2023

Empowering Practical Root Cause Analysis by Large Language Models for Cloud Incidents.

Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xuedong Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo Ghosh, Xuchao Zhang, Chaoyun Zhang, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang

CoRR, 2023

Knowledge-enhanced Neural Machine Reasoning: A Review.

Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao

CoRR, 2023

LANS: Large-scale Arabic News Summarization Corpus.

Abdulaziz Alhamadani, Xuchao Zhang, Jianfeng He, Aadyant Khatri, Chang-Tien Lu

Proceedings of ArabicNLP 2023, Singapore (Hybrid), December 7, 2023, 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

Proceedings of the 2023 USENIX Annual Technical Conference, 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

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models.

Toufique Ahmed, Supriyo Ghosh, Chetan Bansal, Thomas Zimmermann, Xuchao Zhang, Saravan Rajmohan

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

Multi-Label Temporal Evidential Neural Networks for Early Event Detection.

Xujiang Zhao, Xuchao Zhang, Chen Zhao, Jin-Hee Cho, Lance M. Kaplan, Dong Hyun Jeong, Audun Jøsang, Haifeng Chen, Feng Chen

Proceedings of the IEEE International Conference on Acoustics, 2023

Open-ended Commonsense Reasoning with Unrestricted Answer Candidates.

Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

TART: Improved Few-shot Text Classification Using Task-Adaptive Reference Transformation.

Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Time Series Contrastive Learning with Information-Aware Augmentations.

Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Corpus-level and Concept-based Explanations for Interpretable Document Classification.

Tian Shi, Xuchao Zhang, Ping Wang, Chandan K. Reddy

ACM Trans. Knowl. Discov. Data, 2022

Online and Distributed Robust Regressions with Extremely Noisy Labels.

Shuo Lei, Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu

ACM Trans. Knowl. Discov. Data, 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

LANS: Large-scale Arabic News Summarization Corpus.

Abdulaziz Alhamadani, Xuchao Zhang, Jianfeng He, Chang-Tien Lu

CoRR, 2022

Uncertainty-Aware Cross-Lingual Transfer with Pseudo Partial Labels.

Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 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

Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event Sequences.

Shengming Zhang, Yanchi Liu, Xuchao Zhang, Wei Cheng, Haifeng Chen, Hui Xiong

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

DeepGAR: Deep Graph Learning for Analogical Reasoning.

Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, Liang Zhao

Proceedings of the IEEE International Conference on Data Mining, 2022

Seed: Sound Event Early Detection Via Evidential Uncertainty.

Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen

Proceedings of the IEEE International Conference on Acoustics, 2022

Cross-Domain Few-Shot Semantic Segmentation.

Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Bowen Du, Chang-Tien Lu

Proceedings of the Computer Vision - ECCV 2022, 2022

Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency Graph.

Liyan Xu, Xuchao Zhang, Bo Zong, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao, Jinho D. Choi

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

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, Jingchao Ni, Haifeng Chen, Liang Zhao

CoRR, 2021

Unsupervised Document Embedding via Contrastive Augmentation.

Dongsheng Luo, Wei Cheng, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Bo Zong, Yanchi Liu, Zhengzhang Chen, Dongjin Song, Haifeng Chen, Xiang Zhang

CoRR, 2021

Unsupervised Concept Representation Learning for Length-Varying Text Similarity.

Xuchao Zhang, Bo Zong, Wei Cheng, Jingchao Ni, Yanchi Liu, Haifeng Chen

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Few-Shot Semantic Segmentation via Prototype Augmentation with Image-Level Annotations.

Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Aspect-based Sentiment Classification via Reinforcement Learning.

Lichen Wang, Bo Zong, Yunyu Liu, Can Qin, Wei Cheng, Wenchao Yu, Xuchao Zhang, Haifeng Chen, Yun Fu

Proceedings of the IEEE International Conference on Data Mining, 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

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation.

Liyan Xu, Xuchao Zhang, Xujiang Zhao, Haifeng Chen, Feng Chen, Jinho D. Choi

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization.

Jingchao Ni, Zhengzhang Chen, Wei Cheng, Bo Zong, Dongjin Song, Yanchi Liu, Xuchao Zhang, Haifeng Chen

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Predicting Hepatoma-Related Genes Based on Representation Learning of PPI network and Gene Ontology Annotations.

Tao Wang, Zhiyuan Shao, Yifu Xiao, Xuchao Zhang, Yitian Chen, Binze Shi, Siyu Chen, Yuxian Wang, Jiajie Peng, Xuequn Shang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Multi-Task Recurrent Modular Networks.

Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series.

Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B. Davidson

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

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

Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations.

Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu

CoRR, 2020

A Concept-based Abstraction-Aggregation Deep Neural Network for Interpretable Document Classification.

Tian Shi, Xuchao Zhang, Ping Wang, Chandan K. Reddy

CoRR, 2020

Temporal Context-Aware Representation Learning for Question Routing.

Xuchao Zhang, Wei Cheng, Bo Zong, Yuncong Chen, Jianwu Xu, Ding Li, Haifeng Chen

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Robust Multi-Target Regression for Correlated Data Corruption.

Xuchao Zhang, Yingwen Shao

Proceedings of the 20th IEEE International Conference on Data Mining, 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

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data.

Xuchao Zhang, Xian Wu, Fanglan Chen, Liang Zhao, Chang-Tien Lu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

TapNet: Multivariate Time Series Classification with Attentional Prototypical Network.

Xuchao Zhang, Yifeng Gao, Jessica Lin, Chang-Tien Lu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation.

Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu

ACM Trans. Knowl. Discov. Data, 2019

Mitigating Uncertainty in Document Classification.

Xuchao Zhang, Fanglan Chen, Chang-Tien Lu, Naren Ramakrishnan

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics.

Chao Huang, Xian Wu, Xuchao Zhang, Chuxu Zhang, Jiashu Zhao, Dawei Yin, Nitesh V. Chawla

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Modeling the Relationship between User Comments and Edits in Document Revision.

Xuchao Zhang, Dheeraj Rajagopal, Michael Gamon, Sujay Kumar Jauhar, Chang-Tien Lu

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Deep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity.

Chao Huang, Xian Wu, Xuchao Zhang, Suwen Lin, Nitesh V. Chawla

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Similarity-Aware Network Embedding with Self-Paced Learning.

Chao Huang, Baoxu Shi, Xuchao Zhang, Xian Wu, Nitesh V. Chawla

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Feature driven learning framework for cybersecurity event detection.

Taoran Ji, Xuchao Zhang, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan

Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

2018

Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator.

Zhiqian Chen, Feng Chen, Rongjie Lai, Xuchao Zhang, Chang-Tien Lu

CoRR, 2018

Water Disaggregation via Shape Features based Bayesian Discriminative Sparse Coding.

Bingsheng Wang, Xuchao Zhang, Chang-Tien Lu, Feng Chen

CoRR, 2018

Distributed Self-Paced Learning in Alternating Direction Method of Multipliers.

Xuchao Zhang, Liang Zhao, Zhiqian Chen, Chang-Tien Lu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Robust Regression via Online Feature Selection Under Adversarial Data Corruption.

Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu

Proceedings of the IEEE International Conference on Data Mining, 2018

Rational Neural Networks for Approximating Graph Convolution Operator on Jump Discontinuities.

Zhiqian Chen, Feng Chen, Rongjie Lai, Xuchao Zhang, Chang-Tien Lu

Proceedings of the IEEE International Conference on Data Mining, 2018

Situation-Based Interpretable Learning for Personality Prediction in Social Media.

Lei Zhang, Liang Zhao, Xuchao Zhang, Wenmo Kong, Zitong Sheng, Chang-Tien Lu

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Robust Regression via Heuristic Hard Thresholding.

Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Multimodal Storytelling via Generative Adversarial Imitation Learning.

Zhiqian Chen, Xuchao Zhang, Arnold P. Boedihardjo, Jing Dai, Chang-Tien Lu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Online and Distributed Robust Regressions Under Adversarial Data Corruption.

Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Spatiotemporal Event Forecasting from Incomplete Hyper-local Price Data.

Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu, Naren Ramakrishnan

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Trendi: Tracking stories in news and microblogs via emerging, evolving and fading topics.

Xuchao Zhang, Liang Zhao, Zhiqian Chen, Arnold P. Boedihardjo, Jing Dai, Chang-Tien Lu

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

TRACES: Generating Twitter stories via shared subspace and temporal smoothness.

Xuchao Zhang, Zhiqian Chen, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

Automatical Storyline Generation with Help from Twitter.

Ting Hua, Xuchao Zhang, Wei Wang, Chang-Tien Lu, Naren Ramakrishnan

Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

Storytelling in heterogeneous Twitter entity network based on hierarchical cluster routing.

Xuchao Zhang, Zhiqian Chen, Weisheng Zhong, Arnold P. Boedihardjo, Chang-Tien Lu

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016