Time-series Insights into the Process of Passing or Failing Online University Courses using Neural-Induced Interpretable Student States. - Byungsoo Jeon; Eyal Shafran; Luke Breitfeller; Jason Levin; Carolyn P. Rosé (EDM, 2019)

Finding Microaggressions in the Wild: A Case for Locating Elusive Phenomena in Social Media Posts. - Luke Breitfeller; Emily P. Ahn; David Jurgens; Yulia Tsvetkov (EMNLP/IJCNLP (1), 2019)

TDDiscourse: A Dataset for Discourse-Level Temporal Ordering of Events. - Aakanksha Naik; Luke Breitfeller; Carolyn P. Rosé (SIGdial, 2019)

Angelfish: Building a Structurally Diverse Clinical Document Corpus. - Guy Divita; Bart Desmet; Ayah Zirikly; Luke Breitfeller; Carolyn P. Rosé (AMIA, 2020)

STAGE: Tool for Automated Extraction of Semantic Time Cues to Enrich Neural Temporal Ordering Models. - Luke Breitfeller; Aakanksha Naik; Carolyn P. Rosé (CoRR, 2021)

Multi-Scale Contrastive Co-Training for Event Temporal Relation Extraction. - Hao-Ren Yao; Luke Breitfeller; Aakanksha Naik; Chunxiao Zhou; Carolyn P. Rosé (CoRR, 2022)

Linguistically-Inspired Neural Coreference Resolution. - Xuanyue Yang; Wenting Ye; Luke Breitfeller; Tianwei Yue; Wenping Wang (Adv. Artif. Intell. Mach. Learn., 2023)

Distilling Multi-Scale Knowledge for Event Temporal Relation Extraction. - Hao-Ren Yao; Luke Breitfeller; Aakanksha Naik; Chunxiao Zhou; Carolyn P. Rosé (CIKM, 2024)