Staff profile

Chapter in book

• Fine-grained Main Ideas Extraction and Clustering of Online Course Reviews
  
  Xiao, C., Shi, L., Cristea, A., Li, Z., & Pan, Z. (2022). Fine-grained Main Ideas Extraction and Clustering of Online Course Reviews. In M. Rodrigo, N. Matsuda, A. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education (pp. 294-306). Springer, Cham. https://doi.org/10.1007/978-3-031-11644-5_24

Conference Paper

• Overview of the BioLaySumm 2025 Shared Task on Lay Summarization of Biomedical Research Articles and Radiology Reports
  
  Xiao, C., Zhao, K., Wang, X., Wu, S., Yan, S., Goldsack, T., Ananiadou, S., Al Moubayed, N., Zhan, L., Cheung, W. K., & Lin, C. (2025). Overview of the BioLaySumm 2025 Shared Task on Lay Summarization of Biomedical Research Articles and Radiology Reports. In D. Demner-Fushman, S. Ananiadou, M. Miwa, & J. Tsujii (Eds.), Proceedings of the 24th Workshop on Biomedical Language Processing (pp. 365-377). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.bionlp-1.31
• Analyzing LLMs' Knowledge Boundary Cognition Across Languages Through the Lens of Internal Representations
  
  Xiao, C., Chan, H. P., Zhang, H., Aljunied, M., Bing, L., Al Moubayed, N., & Rong, Y. (2025). Analyzing LLMs’ Knowledge Boundary Cognition Across Languages Through the Lens of Internal Representations. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 24099-24115). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.acl-long.1174
• SciMMIR: Benchmarking Scientific Multi-modal Information Retrieval
  
  Wu, S., Li, Y., Zhu, K., Zhang, G., Liang, Y., Ma, K., Xiao, C., Zhang, H., Yang, B., Chen, W., Huang, W., Al Moubayed, N., Fu, J., & Lin, C. (2024). SciMMIR: Benchmarking Scientific Multi-modal Information Retrieval. In Findings of the Association for Computational Linguistics: ACL 2024 (pp. 12560-12574). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-acl.746
• Length is a Curse and a Blessing for Document-level Semantics
  
  Xiao, C., Li, Y., Hudson, G. T., Lin, C., & Al Moubayed, N. (2023). Length is a Curse and a Blessing for Document-level Semantics. Presented at The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), Singapore.

Journal Article

• Adversarial Defence without Adversarial Defence: Enhancing Language Model Robustness via Instance-level Principal Component Removal
  
  Wang, Y., Xiao, C., Li, Y., Middleton, S. E., Al Moubayed, N., & Lin, C. (in press). Adversarial Defence without Adversarial Defence: Enhancing Language Model Robustness via Instance-level Principal Component Removal. Transactions of the Association for Computational Linguistics.