Data Science in Service of Performing Arts: Applying Machine Learning to Predicting Audience Preferences. - Jacob D. Abernethy; Cyrus Anderson; Alex Chojnacki; Chengyu Dai; John Dryden; Eric M. Schwartz; Wenbo Shen; Jonathan C. Stroud; Laura Wendlandt; Sheng Yang; Daniel T. Zhang (CoRR, 2016)

Multimodal Analysis and Prediction of Latent User Dimensions. - Laura Wendlandt; Rada Mihalcea; Ryan L. Boyd; James W. Pennebaker (SocInfo (1), 2017)

Factors Influencing the Surprising Instability of Word Embeddings. - Laura Wendlandt; Jonathan K. Kummerfeld; Rada Mihalcea (NAACL-HLT, 2018)

Entity and Event Extraction from Scratch Using Minimal Training Data. - Laura Wendlandt; Steven R. Wilson 001; Oana Ignat; Charles Welch; Li Zhang 039; Mingzhe Wang; Jia Deng 001; Rada Mihalcea (TAC, 2018)

Identifying Visible Actions in Lifestyle Vlogs. - Oana Ignat; Laura Burdick; Jia Deng 001; Rada Mihalcea (ACL (1), 2019)

Building a Flexible Knowledge Graph to Capture Real-World Events. - Laura Burdick; Oana Ignat; Yiming Zhang; Rada Mihalcea; Mingzhe Wang; Steve Wilson 002; Yumou Wei; Jia Deng 001 (TAC, 2019)

Understanding Word Embedding Stability Across Languages and Applications. - Laura Burdick (2020)

Analyzing the Surprising Variability in Word Embedding Stability Across Languages. - Laura Burdick; Jonathan K. Kummerfeld; Rada Mihalcea (EMNLP (1), 2021)

Analyzing Connections Between User Attributes, Images, and Text. - Laura Burdick; Rada Mihalcea; Ryan L. Boyd; James W. Pennebaker (Cogn. Comput., 2021)

Using Paraphrases to Study Properties of Contextual Embeddings. - Laura Burdick; Jonathan K. Kummerfeld; Rada Mihalcea (NAACL-HLT, 2022)