Xujiang Zhao

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 47

Top Topics

Dempster Shafer

Early Detection

Top Venues

Publications

Xujiang Zhao, Chen Zhao, Feng Chen, Jin-Hee Cho, Wei Hua, Haifeng Chen
3rd Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM). KDD (2024)
Nan Zhang, Yanchi Liu, Xujiang Zhao, Wei Cheng, Runxue Bao, Rui Zhang, Prasenjit Mitra, Haifeng Chen
Pruning as a Domain-specific LLM Extractor. CoRR (2024)
Chen Ling, Xujiang Zhao, Xuchao Zhang, Wei Cheng, Yanchi Liu, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen
Uncertainty Quantification for In-Context Learning of Large Language Models. NAACL-HLT (2024)
Zhen Guo, Zelin Wan, Qisheng Zhang, Xujiang Zhao, Qi Zhang, Lance M. Kaplan, Audun Jøsang, Dong Hyun Jeong, Feng Chen, Jin-Hee Cho
A survey on uncertainty reasoning and quantification in belief theory and its application to deep learning. Inf. Fusion 101 (2024)
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
Uncertainty Decomposition and Quantification for In-Context Learning of Large Language Models. CoRR (2024)
Chengyuan Deng, Zhengzhang Chen, Xujiang Zhao, Haoyu Wang, Junxiang Wang, Haifeng Chen, Jie Gao
RIO-CPD: A Riemannian Geometric Method for Correlation-aware Online Change Point Detection. CoRR (2024)
Junji Jiang, Chen Ling, Hongyi Li, Guangji Bai, Xujiang Zhao, Liang Zhao
Quantifying uncertainty in graph neural network explanations. Frontiers Big Data 7 (2024)
Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao
Open-ended Commonsense Reasoning with Unrestricted Answer Candidates. EMNLP (Findings) (2023)
Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao, Haifeng Chen
Adaptation Speed Analysis for Fairness-aware Causal Models. CoRR (2023)
Xianjun Yang, Wei Cheng, Xujiang Zhao, Linda R. Petzold, Haifeng Chen
Dynamic Prompting: A Unified Framework for Prompt Tuning. CoRR (2023)
Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao
Open-ended Commonsense Reasoning with Unrestricted Answer Scope. CoRR (2023)
Xujiang Zhao, Chen Zhao, Feng Chen, Jin-Hee Cho, Haifeng Chen
2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making. KDD (2023)
Weili Shi, Xueying Yang, Xujiang Zhao, Haifeng Chen, Zhiqiang Tao, Sheng Li
Calibrate Graph Neural Networks under Out-of-Distribution Nodes via Deep Q-learning. CIKM (2023)
Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao
Knowledge-enhanced Neural Machine Reasoning: A Review. CoRR (2023)
Xujiang Zhao, Xuchao Zhang, Chen Zhao, Jin-Hee Cho, Lance M. Kaplan, Dong Hyun Jeong, Audun Jøsang, Haifeng Chen, Feng Chen
Multi-Label Temporal Evidential Neural Networks for Early Event Detection. ICASSP (2023)
Chen Ling, Xujiang Zhao, Xuchao Zhang, Yanchi Liu, Wei Cheng, Haoyu Wang, Zhengzhang Chen, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao
Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty. CoRR (2023)
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
Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models. CoRR (2023)
Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao, Haifeng Chen
Adaptation Speed Analysis for Fairness-aware Causal Models. CIKM (2023)
Yijia Xiao, Yiqiao Jin, Yushi Bai, Yue Wu, Xianjun Yang, Xiao Luo, Wenchao Yu, Xujiang Zhao, Yanchi Liu, Haifeng Chen, Wei Wang, Wei Cheng
Large Language Models Can Be Good Privacy Protection Learners. CoRR (2023)
Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen
Pursuing Counterfactual Fairness via Sequential Autoencoder Across Domains. CoRR (2023)
Xujiang Zhao
Multidimensional Uncertainty Quantification for Deep Neural Networks. CoRR (2023)
Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen
Layer Adaptive Deep Neural Networks for Out-of-Distribution Detection. PAKDD (2) (2022)
Xueying Yang, Jiamian Wang, Xujiang Zhao, Sheng Li, Zhiqiang Tao
Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty. CIKM (2022)
Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen
SEED: Sound Event Early Detection via Evidential Uncertainty. CoRR (2022)
Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen
Seed: Sound Event Early Detection Via Evidential Uncertainty. ICASSP (2022)
Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen
Layer Adaptive Deep Neural Networks for Out-of-distribution Detection. CoRR (2022)
Xujiang Zhao, KrishnaTeja Killamsetty, Rishabh K. Iyer, Feng Chen
How Out-of-Distribution Data Hurts Semi-Supervised Learning. ICDM (2022)
Zhen Guo, Zelin Wan, Qisheng Zhang, Xujiang Zhao, Feng Chen, Jin-Hee Cho, Qi Zhang, Lance M. Kaplan, Dong H. Jeong, Audun Jøsang
A Survey on Uncertainty Reasoning and Quantification for Decision Making: Belief Theory Meets Deep Learning. CoRR (2022)
KrishnaTeja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. CoRR (2021)
Zhuoyi Wang, Yuqiao Chen, Chen Zhao, Yu Lin, Xujiang Zhao, Hemeng Tao, Yigong Wang, Latifur Khan
CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining. WWW (2021)
Liyan Xu, Xuchao Zhang, Xujiang Zhao, Haifeng Chen, Feng Chen, Jinho D. Choi
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation. CoRR (2021)
Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen
Multidimensional Uncertainty-Aware Evidential Neural Networks. AAAI (2021)
Liyan Xu, Xuchao Zhang, Xujiang Zhao, Haifeng Chen, Feng Chen, Jinho D. Choi
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation. EMNLP (1) (2021)
KrishnaTeja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. NeurIPS (2021)
Xujiang Zhao, Feng Chen, Shu Hu, Jin-Hee Cho
Uncertainty Aware Semi-Supervised Learning on Graph Data. CoRR (2020)
Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen
Multidimensional Uncertainty-Aware Evidential Neural Networks. CoRR (2020)
Weishi Shi, Xujiang Zhao, Feng Chen, Qi Yu
Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning. NeurIPS (2020)
Xujiang Zhao, Feng Chen, Shu Hu, Jin-Hee Cho
Uncertainty Aware Semi-Supervised Learning on Graph Data. NeurIPS (2020)
Xujiang Zhao, KrishnaTeja Killamsetty, Rishabh K. Iyer, Feng Chen
Robust Semi-Supervised Learning with Out of Distribution Data. CoRR (2020)
Xujiang Zhao, Yuzhe Ou, Lance M. Kaplan, Feng Chen, Jin-Hee Cho
Quantifying Classification Uncertainty using Regularized Evidential Neural Networks. CoRR (2019)
Adil Alim, Xujiang Zhao, Jin-Hee Cho, Feng Chen
Uncertainty-Aware Opinion Inference Under Adversarial Attacks. IEEE BigData (2019)
Xujiang Zhao, Shu Hu, Jin-Hee Cho, Feng Chen
Uncertainty-based Decision Making Using Deep Reinforcement Learning. FUSION (2019)
Xujiang Zhao, Feng Chen, Jin-Hee Cho
Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data. CoRR (2019)
Xujiang Zhao, Feng Chen, Jin-Hee Cho
Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data. IEEE BigData (2018)
Xujiang Zhao, Feng Chen, Jin-Hee Cho
Uncertainty-Based Opinion Inference on Network Data Using Graph Convolutional Neural Networks. MILCOM (2018)
Xujiang Zhao, Feng Chen, Jin-Hee Cho
Deep Learning Based Scalable Inference of Uncertain Opinions. ICDM (2018)
Xujiang Zhao, Shouhong Wan, Chang Zou, Xingyue Li, Li Yan
Object Detection Based on Deep Feature for Optical Remote Sensing Images. GSKI (1) (2017)