Xiaoli Wang

Orcid: 0000-0001-9336-1013

Affiliations:
  • Nanjing University of Science and Technology, School of Computer Science and Engineering, Nanjing, China


According to our database1, Xiaoli Wang authored at least 15 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
How Far Are We from Predicting Missing Modalities with Foundation Models?
CoRR, June, 2025

Graph-in-graph discriminative feature enhancement network for fine-grained visual classification.
Appl. Intell., January, 2025

An innovative multi-view collaborative optimization framework for Weighted Naive Bayes.
Knowl. Based Syst., 2025

Knowledge Bridger: Towards Training-Free Missing Modality Completion.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Global-Semantic Alignment Distillation for Partial Multi-view Classification.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Computer vision-driven forest wildfire and smoke recognition via IoT drone cameras.
Wirel. Networks, November, 2024

A Clustering-Guided Contrastive Fusion for Multi-View Representation Learning.
IEEE Trans. Circuits Syst. Video Technol., April, 2024

Knowledge distillation-driven semi-supervised multi-view classification.
Inf. Fusion, March, 2024

Trusted Semi-Supervised Multi-View Classification With Contrastive Learning.
IEEE Trans. Multim., 2024

DVF:Multi-agent Q-learning with difference value factorization.
Knowl. Based Syst., 2024

Adversarially attack feature similarity for fine-grained visual classification.
Appl. Soft Comput., 2024

Rethinking Multi-View Representation Learning via Distilled Disentangling.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Disentangling Multi-view Representations Beyond Inductive Bias.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

2022
MMatch: Semi-Supervised Discriminative Representation Learning for Multi-View Classification.
IEEE Trans. Circuits Syst. Video Technol., 2022

A Clustering-guided Contrastive Fusion for Multi-view Representation Learning.
CoRR, 2022


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