| 2026 | AAAI | ESG-Bench: Benchmarking Long-Context ESG Reports for Hallucination Mitigation. | Siqi Sun, Ben Peng Wu, Mali Jin, Peizhen Bai, Hanpei Zhang, Xingyi Song |
| 2025 | ACL | Efficient Annotator Reliability Assessment with EffiARA. | Owen Cook, Jake Vasilakes, Ian Roberts, Xingyi Song |
| 2025 | ICWSM | A Dataset for Analysing News Framing in Chinese Media. | Owen Cook, Yida Mu, Xinye Yang, Xingyi Song, Kalina Bontcheva |
| 2025 | NAACL | Efficient Annotator Reliability Assessment and Sample Weighting for Knowledge-Based Misinformation Detection on Social Media. | Owen Cook, Charlie Grimshaw, Ben Peng Wu, Sophie Dillon, Jack Hicks, Luke Jones, Thomas Smith, Matyas Szert, Xingyi Song |
| 2024 | COLING | Identifying and Aligning Medical Claims Made on Social Media with Medical Evidence. | Anthony James Hughes, Xingyi Song |
| 2024 | COLING | Large Language Models Offer an Alternative to the Traditional Approach of Topic Modelling. | Yida Mu, Chun Dong, Kalina Bontcheva, Xingyi Song |
| 2024 | COLING | Examining Temporalities on Stance Detection towards COVID-19 Vaccination. | Yida Mu, Mali Jin, Kalina Bontcheva, Xingyi Song |
| 2024 | COLING | Examining the Limitations of Computational Rumor Detection Models Trained on Static Datasets. | Yida Mu, Xingyi Song, Kalina Bontcheva, Nikolaos Aletras |
| 2024 | COLING | Navigating Prompt Complexity for Zero-Shot Classification: A Study of Large Language Models in Computational Social Science. | Yida Mu, Ben P. Wu, William Thorne, Ambrose Robinson, Nikolaos Aletras, Carolina Scarton, Kalina Bontcheva, Xingyi Song |
| 2024 | ECIR | The CLEF-2024 CheckThat! Lab: Check-Worthiness, Subjectivity, Persuasion, Roles, Authorities, and Adversarial Robustness. | Alberto Barrn-Cedeo, Firoj Alam, Tanmoy Chakraborty, Tamer Elsayed, Preslav Nakov, Piotr Przybyla, Julia Maria Stru, Fatima Haouari, Maram Hasanain, Federico Ruggeri, Xingyi Song, Reem Suwaileh |
| 2024 | EMNLP | Enhancing Data Quality through Simple De-duplication: Navigating Responsible Computational Social Science Research. | Yida Mu, Mali Jin, Xingyi Song, Nikolaos Aletras |
| 2023 | EACL | GATE Teamware 2: An open-source tool for collaborative document classification annotation. | David Wilby, Twin Karmakharm, Ian Roberts, Xingyi Song, Kalina Bontcheva |
| 2023 | EMNLP | Don't waste a single annotation: improving single-label classifiers through soft labels. | Ben Wu, Yue Li, Yida Mu, Carolina Scarton, Kalina Bontcheva, Xingyi Song |
| 2023 | ICWSM | VaxxHesitancy: A Dataset for Studying Hesitancy towards COVID-19 Vaccination on Twitter. | Yida Mu, Mali Jin, Charlie Grimshaw, Carolina Scarton, Kalina Bontcheva, Xingyi Song |
| 2023 | RANLP | Categorising Fine-to-Coarse Grained Misinformation: An Empirical Study of the COVID-19 Infodemic. | Ye Jiang, Xingyi Song, Carolina Scarton, Iknoor Singh, Ahmet Aker, Kalina Bontcheva |
| 2023 | RANLP | Classification-Aware Neural Topic Model Combined with Interpretable Analysis - for Conflict Classification. | Tianyu Liang, Yida Mu, Soonho Kim, Darline Kengne Kuate, Julie Lang, Rob Vos, Xingyi Song |
| 2023 | RANLP | Classifying COVID-19 Vaccine Narratives. | Yue Li, Carolina Scarton, Xingyi Song, Kalina Bontcheva |
| 2020 | ECAI | Comparing Topic-Aware Neural Networks for Bias Detection of News. | Ye Jiang, Yimin Wang, Xingyi Song, Diana Maynard |
| 2020 | LREC | RP-DNN: A Tweet Level Propagation Context Based Deep Neural Networks for Early Rumor Detection in Social Media. | Jie Gao, Sooji Han, Xingyi Song, Fabio Ciravegna |
| 2020 | LREC | Using Deep Neural Networks with Intra- and Inter-Sentence Context to Classify Suicidal Behaviour. | Xingyi Song, Johnny Downs, Sumithra Velupillai, Rachel Holden, Maxim Kikoler, Kalina Bontcheva, Rina Dutta, Angus Roberts |
| 2018 | EMNLP | A Deep Neural Network Sentence Level Classification Method with Context Information. | Xingyi Song, Johann Petrak, Angus Roberts |
| 2017 | EMNLP | Comparing Attitudes to Climate Change in the Media using sentiment analysis based on Latent Dirichlet Allocation. | Ye Jiang, Xingyi Song, Jackie Harrison, Shaun Quegan, Diana Maynard |
| 2014 | EAMT | Data selection for discriminative training in statistical machine translation. | Xingyi Song, Lucia Specia, Trevor Cohn |