2 citations · 4 across the 16 of their papers we have counts for
19 papers
Evaluating Extremely Low-Resource Machine Translation: A Comparative Study of ChrF++ and BLEU Metrics
Sanjeev Kumar, Preethi Jyothi, Pushpak Bhattacharyya
Evaluating machine translation (MT) quality in extremely low-resource language (ELRL) scenarios poses unique challenges, as widely used metrics such as BLEU, effective in high-reso…
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…
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…
Looks can be Deceptive: Distinguishing Repetition Disfluency from Reduplication
Arif Ahmad, Mothika Gayathri Khyathi, Pushpak Bhattacharyya
Reduplication and repetition, though similar in form, serve distinct linguistic purposes. Reduplication is a deliberate morphological process used to express grammatical, semantic,…
Beyond Aesthetics: Cultural Competence in Text-to-Image Models
Nithish Kannen, Arif Ahmad, Marco Andreetto +5
Text-to-Image (T2I) models are being increasingly adopted in diverse global communities where they create visual representations of their unique cultures. Current T2I benchmarks pr…
CoSTA: Code-Switched Speech Translation using Aligned Speech-Text Interleaving
Bhavani Shankar, Preethi Jyothi, Pushpak Bhattacharyya
Code-switching is a widely prevalent linguistic phenomenon in multilingual societies like India. Building speech-to-text models for code-switched speech is challenging due to limit…
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…
Product Description and QA Assisted Self-Supervised Opinion Summarization
Tejpalsingh Siledar, Rupasai Rangaraju, Sankara Sri Raghava Ravindra Muddu +7
In e-commerce, opinion summarization is the process of summarizing the consensus opinions found in product reviews. However, the potential of additional sources such as product des…
IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context
Nihar Ranjan Sahoo, Pranamya Prashant Kulkarni, Narjis Asad +4
The pervasive influence of social biases in language data has sparked the need for benchmark datasets that capture and evaluate these biases in Large Language Models (LLMs). Existi…
Transformers are Expressive, But Are They Expressive Enough for Regression?
Swaroop Nath, Harshad Khadilkar, Pushpak Bhattacharyya
Transformers have become pivotal in Natural Language Processing, demonstrating remarkable success in applications like Machine Translation and Summarization. Given their widespread…
Leveraging Domain Knowledge for Efficient Reward Modelling in RLHF: A Case-Study in E-Commerce Opinion Summarization
Swaroop Nath, Tejpalsingh Siledar, Sankara Sri Raghava Ravindra Muddu +8
Reinforcement Learning from Human Feedback (RLHF) has become a dominating strategy in aligning Language Models (LMs) with human values/goals. The key to the strategy is learning a…
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…
Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement Learning
Swaroop Nath, Harshad Khadilkar, Pushpak Bhattacharyya
Query-focused Summarization (QfS) deals with systems that generate summaries from document(s) based on a query. Motivated by the insight that Reinforcement Learning (RL) provides a…
DISCO: A Large Scale Human Annotated Corpus for Disfluency Correction in Indo-European Languages
Vineet Bhat, Preethi Jyothi, Pushpak Bhattacharyya
Disfluency correction (DC) is the process of removing disfluent elements like fillers, repetitions and corrections from spoken utterances to create readable and interpretable text.…