To Burst or Not to Burst: Generating and Quantifying Improbable Text
To Burst or Not to Burst: Generating and Quantifying Improbable Text. K Sasse, E Kayi, S Barham, E Staley - GEM Workshop @ EMNLP, 2023.
To Burst or Not to Burst: Generating and Quantifying Improbable Text. K Sasse, E Kayi, S Barham, E Staley - GEM Workshop @ EMNLP, 2023.
Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models. C Aguirre, K Sasse, I Cachola, M Dredze - Third Workshop on NLP for Positive Impact @ EMNLP 2024, 2024.
Wait, but Tylenol is Acetaminophen Investigating and Improving Language Models Ability to Resist Requests for Misinformation. S Chen, M Gao, K Sasse, T Hartvigsen, B Anthony, L Fan, H Aerts, J Gallifant, D Bitterman -- arXiv preprint arXiv:2409.20385, 2024.
Disease Entity Recognition and Normalization is Improved with Large Language Model Derived Synthetic Normalized Mentions. K Sasse, S Vadlakonda, R Kennedy, J Osborne - arXiv preprint arXiv:2410.07951, 2024.
Mapping Bias in Vision Language Models: Signposts, Pitfalls, and the Road Ahead. K Sasse, S Chen, J Pond, D Bitterman, J Osborne - arXiv preprint arXiv:2410.13146, 2024.
Understanding the determinants of vaccine hesitancy in the United States: A comparison of social surveys and social media. K Sasse, R Mahabir, O Gkountouna, A Crooks, A Croitoru - PLOS ONE, 2024.
Talk at DeclMed 2023, Seattle, Washington
Presentation at AMIA 2024 Annual Symposium, San Francisco, California
Presentation at AMIA 2024 Annual Symposium, San Francisco, California