2 citations · 2 across the 9 of their papers we have counts for
9 papers
Knowing When Not to Predict: Self Supervised Learning and Abstention for Safer DR Screening
Muskaan Chopra, Lorenz Sparrenberg, Jan H. Terheyden +1
Self-supervised learning (SSL) is now a standard way to pretrain medical image models, but performance is still mostly judged by downstream accuracy. For safety-critical screening…
Towards Reliable Machine Translation: Scaling LLMs for Critical Error Detection and Safety
Muskaan Chopra, Lorenz Sparrenberg, Rafet Sifa
Machine Translation (MT) plays a pivotal role in cross-lingual information access, public policy communication, and equitable knowledge dissemination. However, critical meaning err…
History Rhymes: Macro-Contextual Retrieval for Robust Financial Forecasting
Sarthak Khanna, Armin Berger, Muskaan Chopra +2
Financial markets are inherently non-stationary: structural breaks and macroeconomic regime shifts often cause forecasting models to fail when deployed out of distribution (OOD). C…
From Retinal Pixels to Patients: Evolution of Deep Learning Research in Diabetic Retinopathy Screening
Muskaan Chopra, Lorenz Sparrenberg, Armin Berger +3
Diabetic Retinopathy (DR) remains a leading cause of preventable blindness, with early detection critical for reducing vision loss worldwide. Over the past decade, deep learning ha…
How Small Can You Go? Compact Language Models for On-Device Critical Error Detection in Machine Translation
Muskaan Chopra, Lorenz Sparrenberg, Sarthak Khanna +1
Large Language Models (LLMs) excel at evaluating machine translation (MT), but their scale and cost hinder deployment on edge devices and in privacy-sensitive workflows. We ask: ho…
SynCED-EnDe 2025: A Synthetic and Curated English - German Dataset for Critical Error Detection in Machine Translation
Muskaan Chopra, Lorenz Sparrenberg, Rafet Sifa
Critical Error Detection (CED) in machine translation aims to determine whether a translation is safe to use or contains unacceptable deviations in meaning. While the WMT21 English…
Learning Self-Supervised Representations for Label Efficient Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus Images
Ekta Gupta, Varun Gupta, Muskaan Chopra +2
This work presents a novel label-efficient selfsupervised representation learning-based approach for classifying diabetic retinopathy (DR) images in cross-domain settings. Most of…
Domain Adaptable Self-supervised Representation Learning on Remote Sensing Satellite Imagery
Muskaan Chopra, Prakash Chandra Chhipa, Gopal Mengi +2
This work presents a novel domain adaption paradigm for studying contrastive self-supervised representation learning and knowledge transfer using remote sensing satellite data. Maj…
Functional Knowledge Transfer with Self-supervised Representation Learning
Prakash Chandra Chhipa, Muskaan Chopra, Gopal Mengi +7
This work investigates the unexplored usability of self-supervised representation learning in the direction of functional knowledge transfer. In this work, functional knowledge tra…