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Xujiang Zhao
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2020 – today
- 2024
- [j2]Junji Jiang, Chen Ling, Hongyi Li, Guangji Bai, Xujiang Zhao, Liang Zhao:
Quantifying uncertainty in graph neural network explanations. Frontiers Big Data 7 (2024) - [j1]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: 101987 (2024) - [c26]Yijia Xiao, Yiqiao Jin, Yushi Bai, Yue Wu, Xianjun Yang, Xiao Luo, Wenchao Yu, Xujiang Zhao, Yanchi Liu, Quanquan Gu, Haifeng Chen, Wei Wang, Wei Cheng:
Large Language Models Can Be Contextual Privacy Protection Learners. EMNLP 2024: 14179-14201 - [c25]Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen:
Towards Counterfactual Fairness-aware Domain Generalization in Changing Environments. IJCAI 2024: 4560-4568 - [c24]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: 6755-6756 - [c23]Nan Zhang, Yanchi Liu, Xujiang Zhao, Wei Cheng, Runxue Bao, Rui Zhang, Prasenjit Mitra, Haifeng Chen:
Pruning as a Domain-specific LLM Extractor. NAACL-HLT (Findings) 2024: 1417-1428 - [c22]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: 3357-3370 - [i25]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 abs/2402.10189 (2024) - [i24]Nan Zhang, Yanchi Liu, Xujiang Zhao, Wei Cheng, Runxue Bao, Rui Zhang, Prasenjit Mitra, Haifeng Chen:
Pruning as a Domain-specific LLM Extractor. CoRR abs/2405.06275 (2024) - [i23]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 abs/2407.09698 (2024) - [i22]Minhua Lin, Zhengzhang Chen, Yanchi Liu, Xujiang Zhao, Zongyu Wu, Junxiang Wang, Xiang Zhang, Suhang Wang, Haifeng Chen:
Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation. CoRR abs/2410.17462 (2024) - [i21]Jonathan Light, Yue Wu, Yiyou Sun, Wenchao Yu, Yanchi Liu, Xujiang Zhao, Ziniu Hu, Haifeng Chen, Wei Cheng:
Scattered Forest Search: Smarter Code Space Exploration with LLMs. CoRR abs/2411.05010 (2024) - [i20]Qiwei Zhao, Xujiang Zhao, Yanchi Liu, Wei Cheng, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Huaxiu Yao, Haifeng Chen:
SAUP: Situation Awareness Uncertainty Propagation on LLM Agent. CoRR abs/2412.01033 (2024) - 2023
- [c21]Yujie Lin
, Chen Zhao
, Minglai Shao
, Xujiang Zhao
, Haifeng Chen
:
Adaptation Speed Analysis for Fairness-aware Causal Models. CIKM 2023: 1421-1430 - [c20]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: 2270-2279 - [c19]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: 8035-8047 - [c18]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: 1-5 - [c17]Xujiang Zhao
, Chen Zhao
, Feng Chen, Jin-Hee Cho, Haifeng Chen
:
2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making. KDD 2023: 5907-5908 - [i19]Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao:
Knowledge-enhanced Neural Machine Reasoning: A Review. CoRR abs/2302.02093 (2023) - [i18]Xianjun Yang, Wei Cheng, Xujiang Zhao, Linda R. Petzold, Haifeng Chen:
Dynamic Prompting: A Unified Framework for Prompt Tuning. CoRR abs/2303.02909 (2023) - [i17]Xujiang Zhao:
Multidimensional Uncertainty Quantification for Deep Neural Networks. CoRR abs/2304.10527 (2023) - [i16]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 abs/2305.18703 (2023) - [i15]Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao, Haifeng Chen:
Adaptation Speed Analysis for Fairness-aware Causal Models. CoRR abs/2308.16879 (2023) - [i14]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 abs/2309.03433 (2023) - [i13]Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen:
Pursuing Counterfactual Fairness via Sequential Autoencoder Across Domains. CoRR abs/2309.13005 (2023) - [i12]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 abs/2310.02469 (2023) - [i11]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 abs/2310.11672 (2023) - 2022
- [c16]Xueying Yang, Jiamian Wang, Xujiang Zhao, Sheng Li, Zhiqiang Tao:
Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty. CIKM 2022: 4640-4644 - [c15]Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen
, Haifeng Chen, Feng Chen:
Seed: Sound Event Early Detection Via Evidential Uncertainty. ICASSP 2022: 3618-3622 - [c14]Xujiang Zhao, KrishnaTeja Killamsetty, Rishabh K. Iyer, Feng Chen:
How Out-of-Distribution Data Hurts Semi-Supervised Learning. ICDM 2022: 763-772 - [c13]Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen:
Layer Adaptive Deep Neural Networks for Out-of-Distribution Detection. PAKDD (2) 2022: 526-538 - [i10]Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen:
SEED: Sound Event Early Detection via Evidential Uncertainty. CoRR abs/2202.02441 (2022) - [i9]Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen:
Layer Adaptive Deep Neural Networks for Out-of-distribution Detection. CoRR abs/2203.00192 (2022) - [i8]Zhen Guo
, Zelin Wan, Qisheng Zhang, Xujiang Zhao, Feng Chen, Jin-Hee Cho, Qi Zhang, Lance M. Kaplan, Dong Hyun Jeong, Audun Jøsang:
A Survey on Uncertainty Reasoning and Quantification for Decision Making: Belief Theory Meets Deep Learning. CoRR abs/2206.05675 (2022) - 2021
- [c12]Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen:
Multidimensional Uncertainty-Aware Evidential Neural Networks. AAAI 2021: 7815-7822 - [c11]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: 6716-6723 - [c10]KrishnaTeja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer:
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. NeurIPS 2021: 14488-14501 - [c9]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: 1351-1362 - [i7]KrishnaTeja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer:
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. CoRR abs/2106.07760 (2021) - [i6]Liyan Xu, Xuchao Zhang, Xujiang Zhao, Haifeng Chen, Feng Chen, Jinho D. Choi:
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation. CoRR abs/2109.00194 (2021) - 2020
- [c8]Weishi Shi, Xujiang Zhao, Feng Chen, Qi Yu
:
Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning. NeurIPS 2020 - [c7]Xujiang Zhao, Feng Chen, Shu Hu, Jin-Hee Cho:
Uncertainty Aware Semi-Supervised Learning on Graph Data. NeurIPS 2020 - [i5]Xujiang Zhao, KrishnaTeja Killamsetty, Rishabh K. Iyer, Feng Chen:
Robust Semi-Supervised Learning with Out of Distribution Data. CoRR abs/2010.03658 (2020) - [i4]Xujiang Zhao, Feng Chen, Shu Hu, Jin-Hee Cho:
Uncertainty Aware Semi-Supervised Learning on Graph Data. CoRR abs/2010.12783 (2020) - [i3]Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen:
Multidimensional Uncertainty-Aware Evidential Neural Networks. CoRR abs/2012.13676 (2020)
2010 – 2019
- 2019
- [c6]Adil Alim, Xujiang Zhao, Jin-Hee Cho, Feng Chen:
Uncertainty-Aware Opinion Inference Under Adversarial Attacks. IEEE BigData 2019: 6-15 - [c5]Xujiang Zhao, Shu Hu, Jin-Hee Cho, Feng Chen:
Uncertainty-based Decision Making Using Deep Reinforcement Learning. FUSION 2019: 1-8 - [i2]Xujiang Zhao, Feng Chen, Jin-Hee Cho:
Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data. CoRR abs/1910.05640 (2019) - [i1]Xujiang Zhao, Yuzhe Ou, Lance M. Kaplan, Feng Chen, Jin-Hee Cho:
Quantifying Classification Uncertainty using Regularized Evidential Neural Networks. CoRR abs/1910.06864 (2019) - 2018
- [c4]Xujiang Zhao, Feng Chen, Jin-Hee Cho:
Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data. IEEE BigData 2018: 1150-1155 - [c3]Xujiang Zhao, Feng Chen, Jin-Hee Cho:
Deep Learning Based Scalable Inference of Uncertain Opinions. ICDM 2018: 807-816 - [c2]Xujiang Zhao, Feng Chen, Jin-Hee Cho:
Uncertainty-Based Opinion Inference on Network Data Using Graph Convolutional Neural Networks. MILCOM 2018: 731-736 - 2017
- [c1]Xujiang Zhao, Shouhong Wan, Chang Zou, Xingyue Li, Li Yan:
Object Detection Based on Deep Feature for Optical Remote Sensing Images. GSKI (1) 2017: 327-335
Coauthor Index

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last updated on 2025-01-20 22:44 CET by the dblp team
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