Dr Xingyi Song

简介

Dr. Xingyi Song is a Lecturer in Computational Media Analysis in the Department of Computer Science at the University of Sheffield, where he is a core member of the Natural Language Processing (NLP) research group and the GATE team.His research focuses on enabling AI to understand and interpret complex data, ranging from human language and digital media to physical machinery and industrial systems, with a particular emphasis on building AI systems that people can trust.Dr. Song actively translates academic research into practical solutions that benefit society and industry. Through knowledge exchange, he co-developed a text analytics platform for the National Health Service (NHS) to help process clinical data and improve patient insights. He also collaborated with the International Food Po

代表成果

• Kaur L, Griffiths AW, Harrison J, Song X & Blackburn D (2026) Navigating diagnosis: UK informal caregivers’ experiences of the dementia assessment journey. Aging & Mental Health. View this article in WRRO
• Jiang Y, Wang T, Xu X, Wang Y, Song X & Maynard D (2025) Cross-modal augmentation for few-shot multimodal fake news detection. Engineering Applications of Artificial Intelligence, 142, 109931-109931.
• Razuvayevskaya O, Wu B, Leite JA, Heppell F, Srba I, Scarton C, Bontcheva K & Song X (2024) Comparison between parameter-efficient techniques and full fine-tuning: a case study on multilingual news article classification. PLoS ONE, 19(5). View this article in WRRO
• Mu Y, Jin M, Bontcheva K & Song X (2024) Examining temporalities on stance detection towards COVID-19 vaccination. 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings, 6732-6738. View this article in WRRO
• Mu Y, Wu BP, Thorne W, Robinson A, Aletras N, Scarton C, Bontcheva K & Song X (2024) Navigating prompt complexity for zero-shot classification: a study of large language models in computational social science. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), 12074-12086. View this article in WRRO
• Mu Y, Song X, Bontcheva K & Aletras N (2024) Examining the limitations of computational rumor detection models trained on static datasets. 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings, 6739-6751. View this article in WRRO
• Mu Y, Dong C, Bontcheva K & Song X (2024) Large language models offer an alternative to the traditional approach of topic modelling. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), 10160-10171. View this article in WRRO
• Mu Y, Jin M, Song X & Aletras N (2024) Enhancing Data Quality through Simple De-duplication: Navigating Responsible Computational Social Science Research.. CoRR, abs/2410.03545.
• Scarton C, Prescott C, Bayliss C, Oakley C, Wright J, Wrigley S & Song X (2024) Message from the Organising Committee. Proceedings of the 25th Annual Conference of the European Association for Machine Translation Eamt 2024, 1, iv-v.
• Scarton C, Oakley C, Prescott C, Wright J, Bayliss C, Wrigley S & Song X (2024) Message from the Organising Committee. Proceedings of the 25th Annual Conference of the European Association for Machine Translation Eamt 2024, 2, iv-v.