Improving Clinical Predictions through Unsupervised Time Series Representation Learning. - Xinrui Lyu; Matthias Hüser; Stephanie L. Hyland; George Zerveas; Gunnar Rätsch (CoRR, 2018)

Brown University at TREC Deep Learning 2019. - George Zerveas; Ruochen Zhang; Leila Kim; Carsten Eickhoff (TREC, 2019)

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 (AMIA, 2020)

A Transformer-based Framework for Multivariate Time Series Representation Learning. - George Zerveas; Srideepika Jayaraman; Dhaval Patel 002; Anuradha Bhamidipaty; Carsten Eickhoff (KDD, 2021)

CODER: An efficient framework for improving retrieval through COntextualized Document Embedding Reranking. - George Zerveas; Navid Rekabsaz; Daniel Cohen; Carsten Eickhoff (CoRR, 2021)

CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking. - George Zerveas; Navid Rekabsaz; Daniel Cohen; Carsten Eickhoff (EMNLP, 2022)

Unsupervised Multivariate Time-Series Transformers for Seizure Identification on EEG. - Ilkay Yildiz Potter; George Zerveas; Carsten Eickhoff; Dominique Duncan (ICMLA, 2022)

Mitigating Bias in Search Results Through Contextual Document Reranking and Neutrality Regularization. - George Zerveas; Navid Rekabsaz; Daniel Cohen; Carsten Eickhoff (SIGIR, 2022)

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model. - Shaden Smith; Mostofa Patwary; Brandon Norick; Patrick LeGresley; Samyam Rajbhandari; Jared Casper; Zhun Liu; Shrimai Prabhumoye; George Zerveas; Vijay Korthikanti; Elton Zheng; Rewon Child; et al. (CoRR, 2022)

CATS: Customizable Abstractive Topic-based Summarization. - Seyed Ali Bahrainian; George Zerveas; Fabio Crestani; Carsten Eickhoff (ACM Trans. Inf. Syst., 2022)

Leveraging Unlabeled Electroencephalographic Data to Predict Neurological Recovery for Comatose Patients Following Cardiac Arrest. - Isaac Sears; Augusto Garcia-Agundez; George Zerveas; William Rudman; Laura Mercurio; Corey E. Ventetuolo; Adeel Abbasi; Carsten Eickhoff (CinC, 2023)

Parameter-efficient Modularised Bias Mitigation via AdapterFusion. - Deepak Kumar; Oleg Lesota; George Zerveas; Daniel Cohen; Carsten Eickhoff; Markus Schedl; Navid Rekabsaz (EACL, 2023)

Enhancing the Ranking Context of Dense Retrieval through Reciprocal Nearest Neighbors. - George Zerveas; Navid Rekabsaz; Carsten Eickhoff (EMNLP, 2023)

Enhancing the Ranking Context of Dense Retrieval Methods through Reciprocal Nearest Neighbors. - George Zerveas; Navid Rekabsaz; Carsten Eickhoff (CoRR, 2023)

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 (CoRR, 2025)