Xujiang Zhao

Orcid: 0000-0003-4950-4018

According to our database¹, Xujiang Zhao authored at least 34 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

A survey on uncertainty reasoning and quantification in belief theory and its application to deep learning.

[BibT_eX]

[DOI]

Inf. Fusion, January, 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

2023

Open-ended Commonsense Reasoning with Unrestricted Answer Scope.

[BibT_eX]

[DOI]

CoRR, 2023

Large Language Models Can Be Good Privacy Protection Learners.

[BibT_eX]

[DOI]

CoRR, 2023

Pursuing Counterfactual Fairness via Sequential Autoencoder Across Domains.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Multidimensional Uncertainty Quantification for Deep Neural Networks.

[BibT_eX]

[DOI]

Xujiang Zhao

CoRR, 2023

Dynamic Prompting: A Unified Framework for Prompt Tuning.

[BibT_eX]

[DOI]

CoRR, 2023

Knowledge-enhanced Neural Machine Reasoning: A Review.

[BibT_eX]

[DOI]

CoRR, 2023

2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

Open-ended Commonsense Reasoning with Unrestricted Answer Candidates.

[BibT_eX]

[DOI]

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

Calibrate Graph Neural Networks under Out-of-Distribution Nodes via Deep Q-learning.

[BibT_eX]

[DOI]

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Adaptation Speed Analysis for Fairness-aware Causal Models.

[BibT_eX]

[DOI]

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

A Survey on Uncertainty Reasoning and Quantification for Decision Making: Belief Theory Meets Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Layer Adaptive Deep Neural Networks for Out-of-Distribution Detection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

How Out-of-Distribution Data Hurts Semi-Supervised Learning.

[BibT_eX]

[DOI]

Xujiang Zhao

KrishnaTeja Killamsetty

Rishabh K. Iyer

Feng Chen

Proceedings of the IEEE International Conference on Data Mining, 2022

Seed: Sound Event Early Detection Via Evidential Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining.

[BibT_eX]

[DOI]

Proceedings of the WWW '21: The Web Conference 2021, 2021

RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning.

[BibT_eX]

[DOI]

KrishnaTeja Killamsetty

Xujiang Zhao

Feng Chen

Rishabh K. Iyer

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

[BibT_eX]

[DOI]

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

Multidimensional Uncertainty-Aware Evidential Neural Networks.

[BibT_eX]

[DOI]

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

2020

Robust Semi-Supervised Learning with Out of Distribution Data.

[BibT_eX]

[DOI]

Xujiang Zhao

KrishnaTeja Killamsetty

Rishabh K. Iyer

Feng Chen

CoRR, 2020

Uncertainty Aware Semi-Supervised Learning on Graph Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Quantifying Classification Uncertainty using Regularized Evidential Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Uncertainty-based Decision Making Using Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 22th International Conference on Information Fusion, 2019

Uncertainty-Aware Opinion Inference Under Adversarial Attacks.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Uncertainty-Based Opinion Inference on Network Data Using Graph Convolutional Neural Networks.

[BibT_eX]

[DOI]

Xujiang Zhao

Feng Chen

Jin-Hee Cho

Proceedings of the 2018 IEEE Military Communications Conference, 2018

Deep Learning Based Scalable Inference of Uncertain Opinions.

[BibT_eX]

[DOI]

Xujiang Zhao

Feng Chen

Jin-Hee Cho

Proceedings of the IEEE International Conference on Data Mining, 2018

Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data.

[BibT_eX]

[DOI]

Xujiang Zhao

Feng Chen

Jin-Hee Cho

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

2017

Object Detection Based on Deep Feature for Optical Remote Sensing Images.

[BibT_eX]

[DOI]

Proceedings of the Geo-Spatial Knowledge and Intelligence - 5th International Conference, 2017

Xujiang Zhao

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