8 papers · 1 filter
Answer Generation for Questions With Multiple Information Sources in E-Commerce
Anand A. Rajasekar, Nikesh Garera
Automatic question answering is an important yet challenging task in E-commerce given the millions of questions posted by users about the product that they are interested in purcha…
LLMs as Architects and Critics for Multi-Source Opinion Summarization
Anuj Attri, Arnav Attri, Pushpak Bhattacharyya +4
Multi-source Opinion Summarization (M-OS) extends beyond traditional opinion summarization by incorporating additional sources of product metadata such as descriptions, key feature…
"This Suits You the Best": Query Focused Comparative Explainable Summarization
Arnav Attri, Anuj Attri, Pushpak Bhattacharyya +4
Product recommendations inherently involve comparisons, yet traditional opinion summarization often fails to provide holistic comparative insights. We propose the novel task of gen…
Why We Feel What We Feel: Joint Detection of Emotions and Their Opinion Triggers in E-commerce
Arnav Attri, Anuj Attri, Pushpak Bhattacharyya +4
Customer reviews on e-commerce platforms capture critical affective signals that drive purchasing decisions. However, no existing research has explored the joint task of emotion de…
Distilling Opinions at Scale: Incremental Opinion Summarization using XL-OPSUMM
Sri Raghava Muddu, Rupasai Rangaraju, Tejpalsingh Siledar +8
Opinion summarization in e-commerce encapsulates the collective views of numerous users about a product based on their reviews. Typically, a product on an e-commerce platform has t…
One Prompt To Rule Them All: LLMs for Opinion Summary Evaluation
Tejpalsingh Siledar, Swaroop Nath, Sankara Sri Raghava Ravindra Muddu +8
Evaluation of opinion summaries using conventional reference-based metrics rarely provides a holistic evaluation and has been shown to have a relatively low correlation with human…