5 papers
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…
Reasoning LLMs in the Medical Domain: A Literature Survey
Armin Berger, Sarthak Khanna, David Berghaus +1
The emergence of advanced reasoning capabilities in Large Language Models (LLMs) marks a transformative development in healthcare applications. Beyond merely expanding functional c…
Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention
Sarthak Khanna, Armin Berger, David Berghaus +3
We propose STONK (Stock Optimization using News Knowledge), a multimodal framework integrating numerical market indicators with sentiment-enriched news embeddings to improve daily…