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cs.CL2025
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…
cs.CL2024
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…
cs.CL2024
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.…