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cs.LG2026
Action-On-Item Preference Flow: A Shared Event Schema for Predictive and Generative Personalization
Parthiv Chatterjee, Kashish Kanjaria, Vashisth Purani +2
A user's movie, news, and dialogue histories differ in their native actions and outputs, yet each interaction supplies evidence that can update user memory. We study whether these…
cs.LG2026
Not All Is Lost: Repairing Lossy User Preference States of Personalization Encoders
Parthiv Chatterjee, Dhiraj Golhar, Ummesalma Diwan +3
Personalization encoders compress evolving interaction histories into preference states used to rank items or condition text generation. A task head operating only on this state ca…
cs.LG2025
Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning
Prateek Chanda, Saral Sureka, Parth Pratim Chatterjee +3
Supervised fine-tuning performance for large language models depends strongly on how training budget is distributed across a heterogeneous set of tasks. In practice, mixtures are o…