21 citations · 72 across the 15 of their papers we have counts for
5 papers · 1 filter
Pearl: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers
Sheshera Mysore, Zhuoran Lu, Mengting Wan +7
Powerful large language models have facilitated the development of writing assistants that promise to significantly improve the quality and efficiency of composition and communicat…
Large Language Model Augmented Narrative Driven Recommendations
Sheshera Mysore, Andrew McCallum, Hamed Zamani
Narrative-driven recommendation (NDR) presents an information access problem where users solicit recommendations with verbose descriptions of their preferences and context, for exa…
LaMP: When Large Language Models Meet Personalization
Alireza Salemi, Sheshera Mysore, Michael Bendersky +1
This paper highlights the importance of personalization in large language models and introduces the LaMP benchmark -- a novel benchmark for training and evaluating language models…
Editable User Profiles for Controllable Text Recommendation
Sheshera Mysore, Mahmood Jasim, Andrew McCallum +1
Methods for making high-quality recommendations often rely on learning latent representations from interaction data. These methods, while performant, do not provide ready mechanism…
How Data Scientists Review the Scholarly Literature
Sheshera Mysore, Mahmood Jasim, Haoru Song +3
Keeping up with the research literature plays an important role in the workflow of scientists - allowing them to understand a field, formulate the problems they focus on, and devel…