Scholar
Xingyi Song
Google Scholar ID: 7seaj48AAAAJ
University of Sheffield
Citations & Impact
Citations
997
H-index
17
i10-index
24
Publications
20
Co-authors
12
list available
Publications
Resume (English only)
Academic Achievements
- - Publications:
- - Cross-modal augmentation for few-shot multimodal fake news detection
- - Enhancing Data Quality through Simple De-duplication: Navigating Responsible Computational Social Science Research
- - Confidence Regulation Neurons in Language Models
- - Examining the Limitations of Computational Rumor Detection Models Trained on Static Datasets
- - Navigating Prompt Complexity for Zero-Shot Classification: A Study of Large Language Models in Computational Social Science
- - Examining Temporalities on Stance Detection Towards COVID-19 Vaccination
- - Large Language Models Offer an Alternative to the Traditional Approach of Topic Modelling
- - Identifying and Aligning Medical Claims Made on Social Media with Medical Evidence
- - Don’t waste a single annotation: improving single-label classifiers through soft labels
Research Experience
- - Machine Translation Specialist: Iconic Translation Machine (2015–2016)
- - Research Associate: Involved in various EU-funded projects (such as Kconnect, Knowmak, Risis2) at the University of Sheffield (2016–2021)
Education
- - Degree: MSc, PhD
- - University: University of Sheffield
- - Supervisor: Not mentioned
- - Time: Not specifically mentioned
- - Major: Natural Language Processing
Background
- - Research Interests: Natural Language Processing, Computational Social Science, Bio-medical Text Analysis, Speech Analysis, and Financial Technology
- - Professional Field: Natural Language Processing, Computational Social Science, Bio-medical Text Analysis, Speech Analysis, and Financial Technology
- - Brief Introduction: Dr. Xingyi Song is a Lecturer in the School of Computer Science at the University of Sheffield, UK. He is also a member of the Natural Language Processing (NLP) Group and the GATE Team. Additionally, he serves as the Chief Scientific Officer at Sentient Machines.
Miscellany
- - Open to Collaboration: Welcomes research and industry collaborations
