Haijun Shan

Orcid: 0000-0001-5693-6084

According to our database1, Haijun Shan authored at least 11 papers between 2012 and 2024.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Graph Interpretation of Image-Text Matching: Link Prediction on Concept-Enhanced Cross-Modal Graph.
Proceedings of the Natural Language Processing and Chinese Computing, 2024

Identity-Driven Multimedia Forgery Detection via Reference Assistance.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

A Soft Contrastive Learning-Based Prompt Model for Few-Shot Sentiment Analysis.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
A Soft Contrastive Learning-based Prompt Model for Few-shot Sentiment Analysis.
CoRR, 2023

Query Structure Modeling for Inductive Logical Reasoning Over Knowledge Graphs.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Constructing Phrase-level Semantic Labels to Form Multi-Grained Supervision for Image-Text Retrieval.
Proceedings of the ICMR '22: International Conference on Multimedia Retrieval, Newark, NJ, USA, June 27, 2022

2021
TCIC: Theme Concepts Learning Cross Language and Vision for Image Captioning.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

An Unsupervised Sampling Approach for Image-Sentence Matching Using Document-level Structural Information.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Keep it Consistent: Topic-Aware Storytelling from an Image Stream via Iterative Multi-agent Communication.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

2019
Keep it Consistent: Topic-Aware Storytelling from an Image Stream via Iterative Multi-agent Communication.
CoRR, 2019

2012
EEG-based motor imagery classification accuracy improves with gradually increased channel number.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012


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