Leixin is a PhD researcher in Computational Linguistics and Natural Language Processing at the University of Tübingen. She is a member of Project C2, Signaling and Interpreting Defectivity in Common Ground: Face-to-Face, Voice-Only, and Text-Only Communication (CRC 1718 Common Ground).
General Interests: Natural Language Processing (NLP), Semantic Representation, Multimodal Large Language Models (LLMs), Explainable Artificial Intelligence (XAI).
Interpretation variation and perspective-aware modeling
Model uncertainty quantification and confidence estimation
Multi-model large language models
Representation learning
M.A. in Computational Linguistics, University of Tübingen
M.Phil. in Linguistics, Trinity College Dublin
Zhang, L., Eger, S., Cheng, Y., ZHAI, W., Belouadi, J., Moafian, F., & Zhao, Z. (2025) ScImage: How good are multimodal large language models at scientific text-to-image generation?. In The Thirteenth International Conference on Learning Representations.
Zhang, L. (2025). Proposal: From One-Fit-All to Perspective Aware Modeling. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop) (pp. 1016-1025).
Zhang, L., Burian, D., John, V., & Bojar, O. (2024). Unveiling Semantic Information in Sentence Embeddings. In Proceedings of the Fifth International Workshop on Designing Meaning Representations @ LREC-COLING 2024 (pp. 39-47).
Zhang, L., & Çöltekin, Ç. (2024). Tübingen-CL at SemEval-2024 Task 1: Ensemble Learning for Semantic Relatedness Estimation. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024) (pp. 1019-1025).