7 papers
Who Will Top the Charts? Multimodal Music Popularity Prediction via Adaptive Fusion of Modality Experts and Temporal Engagement Modeling
Yash Choudhary, Preeti Rao, Pushpak Bhattacharyya
Predicting a song's commercial success prior to its release remains an open and critical research challenge for the music industry. Early prediction of music popularity informs str…
Lyrics Matter: Exploiting the Power of Learnt Representations for Music Popularity Prediction
Yash Choudhary, Preeti Rao, Pushpak Bhattacharyya
Accurately predicting music popularity is a critical challenge in the music industry, offering benefits to artists, producers, and streaming platforms. Prior research has largely f…
Nyay-Darpan: Enhancing Decision Making Through Summarization and Case Retrieval for Consumer Law in India
Swapnil Bhattacharyya, Harshvivek Kashid, Shrey Ganatra +6
AI-based judicial assistance and case prediction have been extensively studied in criminal and civil domains, but remain largely unexplored in consumer law, especially in India. In…
Enhancing Food-Domain Question Answering with a Multimodal Knowledge Graph: Hybrid QA Generation and Diversity Analysis
Srihari K B, Pushpak Bhattacharyya
We propose a unified food-domain QA framework that combines a large-scale multimodal knowledge graph (MMKG) with generative AI. Our MMKG links 13,000 recipes, 3,000 ingredients, 14…
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…