April 2, 2024, 7:51 p.m. | Haoyuan Li, Snigdha Chaturvedi

cs.CL updates on arXiv.org arxiv.org

arXiv:2404.00217v1 Announce Type: new
Abstract: Opinion summarization aims to generate concise summaries that present popular opinions of a large group of reviews. However, these summaries can be too generic and lack supporting details. To address these issues, we propose a new paradigm for summarizing reviews, rationale-based opinion summarization. Rationale-based opinion summaries output the representative opinions as well as one or more corresponding rationales. To extract good rationales, we define four desirable properties: relatedness, specificity, popularity, and diversity and present a …

arxiv cs.cl opinion summarization type

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Machine Learning Engineer

@ Apple | Sunnyvale, California, United States