1 citations · 1 across the 5 of their papers we have counts for
7 papers
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…
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…
HalluPrism: When Multimodal Uncertainty Should Diagnose, Not Decide
Aman Prakash, Sourish Dasgupta, Tanmoy Chakraborty
Multimodal Large Language Models (MLLMs) can assign similar confidence to answers that fail for different reasons. We propose HalluPrism, a behavioral diagnostic that re-runs an an…
Polaris: Coupled Orbital Polar Embeddings for Hierarchical Concept Learning
Sahil Mishra, Srinitish Srinivasan, Sourish Dasgupta +1
Real-world knowledge is often organized as hierarchies such as product taxonomies, medical ontologies, and label trees, yet learning hierarchical representations is challenging due…
Diversity Augmentation of Dynamic User Preference Data for Boosting Personalized Text Summarizers
Parthiv Chatterjee, Shivam Sonawane, Amey Hengle +3
Document summarization enables efficient extraction of user-relevant content but is inherently shaped by individual subjectivity, making it challenging to identify subjective salie…
Are Large Language Models In-Context Personalized Summarizers? Get an iCOPERNICUS Test Done!
Divya Patel, Pathik Patel, Ankush Chander +2
Large Language Models (LLMs) have succeeded considerably in In-Context-Learning (ICL) based summarization. However, saliency is subject to the users' specific preference histories.…
PerSEval: Assessing Personalization in Text Summarizers
Sourish Dasgupta, Ankush Chander, Parth Borad +2
Personalized summarization models cater to individuals' subjective understanding of saliency, as represented by their reading history and current topics of attention. Existing pers…