Ye Jiang

Orcid: 0000-0002-6683-0205

Affiliations:
  • Qingdao University of Science and Technology (QUST), Qingdao, China
  • University of Sheffield, UK (PhD 2021)


According to our database1, Ye Jiang authored at least 21 papers between 2017 and 2025.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
QUST_NLP at SemEval-2025 Task 7: A Three-Stage Retrieval Framework for Monolingual and Crosslingual Fact-Checked Claim Retrieval.
CoRR, June, 2025

IMFND: In-context multimodal fake news detection with large visual-language models.
Knowl. Based Syst., 2025

Cross-modal augmentation for few-shot multimodal fake news detection.
Eng. Appl. Artif. Intell., 2025

AMPLE: Emotion-Aware Multimodal Fusion Prompt Learning for Fake News Detection.
Proceedings of the MultiMedia Modeling, 2025

2024
Instruction Tuning Vs. In-Context Learning: Revisiting Large Language Models in Few-Shot Computational Social Science.
CoRR, 2024

Team QUST at SemEval-2024 Task 8: A Comprehensive Study of Monolingual and Multilingual Approaches for Detecting AI-generated Text.
Proceedings of the 18th International Workshop on Semantic Evaluation, 2024

2023
Similarity-Aware Multimodal Prompt Learning for fake news detection.
Inf. Sci., November, 2023

Topic-aware hierarchical multi-attention network for text classification.
Int. J. Mach. Learn. Cybern., May, 2023

A Large-Scale Comparative Study of Accurate COVID-19 Information versus Misinformation.
CoRR, 2023

Dual-grained Text-Image Olfactory Matching Model with Mutual Promotion Stages.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Team QUST at SemEval-2023 Task 3: A Comprehensive Study of Monolingual and Multilingual Approaches for Detecting Online News Genre, Framing and Persuasion Techniques.
Proceedings of the The 17th International Workshop on Semantic Evaluation, 2023

Categorising Fine-to-Coarse Grained Misinformation: An Empirical Study of the COVID-19 Infodemic.
Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, 2023

Ensemble Pre-trained Multimodal Models for Image-text Retrieval in the NewsImages MediaEval 2023.
Proceedings of the Working Notes Proceedings of the MediaEval 2023 Workshop, 2023

Integrated Multi-stage Contextual Attention Network for Text-Image Matching.
Proceedings of the Working Notes Proceedings of the MediaEval 2023 Workshop, 2023

2022
Fake News Detection Based on Multi-Modal Classifier Ensemble.
Proceedings of the MAD@ICMR 2022: Proceedings of the 1st International Workshop on Multimedia AI against Disinformation, Newark, NJ, USA, June 27, 2022

HFFD: Hybrid Fusion Based Multimodal Flood Relevance Detection.
Proceedings of the Working Notes Proceedings of the MediaEval 2022 Workshop, 2022

2021
Categorising Fine-to-Coarse Grained Misinformation: An Empirical Study of COVID-19 Infodemic.
CoRR, 2021

2020
Classification Aware Neural Topic Model and its Application on a New COVID-19 Disinformation Corpus.
CoRR, 2020

Comparing Topic-Aware Neural Networks for Bias Detection of News.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
Team Bertha von Suttner at SemEval-2019 Task 4: Hyperpartisan News Detection using ELMo Sentence Representation Convolutional Network.
Proceedings of the 13th International Workshop on Semantic Evaluation, 2019

2017
Comparing Attitudes to Climate Change in the Media using sentiment analysis based on Latent Dirichlet Allocation.
Proceedings of the 2017 Workshop: Natural Language Processing meets Journalism, 2017


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