5 papers
Bandit Guided Submodular Curriculum for Adaptive Subset Selection
Prateek Chanda, Prayas Agrawal, Saral Sureka +3
Traditional curriculum learning proceeds from easy to hard samples, yet defining a reliable notion of difficulty remains elusive. Prior work has used submodular functions to induce…
Bayesian Coreset Optimization for Personalized Federated Learning
Prateek Chanda, Shrey Modi, Ganesh Ramakrishnan
In a distributed machine learning setting like Federated Learning where there are multiple clients involved which update their individual weights to a single central server, often…
Enhancing Multi-Image Question Answering via Submodular Subset Selection
Aaryan Sharma, Shivansh Gupta, Samar Agarwal +2
Large multimodal models (LMMs) have achieved high performance in vision-language tasks involving single image but they struggle when presented with a collection of multiple images…
FairPO: Robust Preference Optimization for Fair Multi-Label Learning
Soumen Kumar Mondal, Prateek Chanda, Akshit Varmora +1
Multi-label classification (MLC) often suffers from performance disparities across labels. We propose \textbf{FairPO}, a framework combining preference-based loss and group-robust…
Early Exit and Multi Stage Knowledge Distillation in VLMs for Video Summarization
Anas Anwarul Haq Khan, Utkarsh Verma, Ganesh Ramakrishnan
We introduce DEEVISum (Distilled Early Exit Vision language model for Summarization), a lightweight, efficient, and scalable vision language model designed for segment wise video s…