| 2025 | EMNLP | Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance. | Reza Esfandiarpoor, George Zerveas, Ruochen Zhang, Macton Mgonzo, Carsten Eickhoff, Stephen H. Bach |
| 2023 | EACL | Parameter-efficient Modularised Bias Mitigation via AdapterFusion. | Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz |
| 2023 | EMNLP | Enhancing the Ranking Context of Dense Retrieval through Reciprocal Nearest Neighbors. | George Zerveas, Navid Rekabsaz, Carsten Eickhoff |
| 2022 | EMNLP | CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking. | George Zerveas, Navid Rekabsaz, Daniel Cohen, Carsten Eickhoff |
| 2022 | ICMLA | Unsupervised Multivariate Time-Series Transformers for Seizure Identification on EEG. | Ilkay Yildiz Potter, George Zerveas, Carsten Eickhoff, Dominique Duncan |
| 2022 | SIGIR | Mitigating Bias in Search Results Through Contextual Document Reranking and Neutrality Regularization. | George Zerveas, Navid Rekabsaz, Daniel Cohen, Carsten Eickhoff |
| 2021 | KDD | A Transformer-based Framework for Multivariate Time Series Representation Learning. | George Zerveas, Srideepika Jayaraman, Dhaval Patel, Anuradha Bhamidipaty, Carsten Eickhoff |
| 2020 | AMIA | Extracting Angina Symptoms from Clinical Notes Using Pre-Trained Transformer Architectures. | Aaron S. Eisman, Nishant R. Shah, Carsten Eickhoff, George Zerveas, Elizabeth S. Chen, Wen-Chih Wu, Indra Neil Sarkar |