IMPerSumm: Information-Modulated User Preference Modeling for Personalized Text Summarization
Parthiv Chatterjee, Dhara Jhaveri, Sourish Dasgupta, Tanmoy Chakraborty
2026Year
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get 7ca17902-c711-4580-99ba-84998d7fb425Related papers
- Beyond Markovian Drifts: Action-Biased Geometric Walks with Memory for Personalized SummarizationParthiv Chatterjee, Asish Joel Batha, Tashvi Patel, Sourish Dasgupta et al.ICLR 2026
- EntSUM: A Data Set for Entity-Centric Extractive SummarizationMounica Maddela, Mayank Kulkarni, Daniel Preotiuc-PietroACL 2022 · 2 citations
- Query-Focused Multimodal Summarization with Gate-Guided Mixture-of-ExpertsJiajun Han, Xuran Yang, Hui ZhangACM MM 2025 · 1 citation
- Multiple Pairwise Ranking Networks for Personalized Video SummarizationYassir Saquil, Da Chen, Yuan He, Chuan Li et al.ICCV 2021 · 26 citations
- Unsupervised Extractive Summarization-Based Representations for Accurate and Explainable Collaborative FilteringReinald Adrian Pugoy, Hung-Yu KaoACL 2021
