2 citations · 3 across the 4 of their papers we have counts for
4 papers
FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching
Sunny Gupta, Nikita Jangid, Shounak Das +1
Domain Generalization (DG) seeks to train models that perform reliably on unseen target domains without access to target data during training. While recent progress in smoothing th…
UniVarFL: Uniformity and Variance Regularized Federated Learning for Heterogeneous Data
Sunny Gupta, Nikita Jangid, Amit Sethi
Federated Learning (FL) often suffers from severe performance degradation when faced with non-IID data, largely due to local classifier bias. Traditional remedies such as global mo…
MHQA: A Diverse, Knowledge Intensive Mental Health Question Answering Challenge for Language Models
Suraj Racha, Prashant Joshi, Anshika Raman +4
Mental health remains a challenging problem all over the world, with issues like depression, anxiety becoming increasingly common. Large Language Models (LLMs) have seen a vast app…
FedStein: Enhancing Multi-Domain Federated Learning Through James-Stein Estimator
Sunny Gupta, Nikita Jangid, Amit Sethi
Federated Learning (FL) facilitates data privacy by enabling collaborative in-situ training across decentralized clients. Despite its inherent advantages, FL faces significant chal…