3 papers
cs.LG2026
Coarse composition suffices: tabular in-context learning for multi-activity antimicrobial peptide profiling
Anuj Pal, Raunak Kumar, Dhruvi Solanki +3
Antimicrobial peptides (AMPs) often act against multiple pathogen classes, making multi-label activity prediction a more realistic screening target than binary antimicrobial classi…
cs.CV2026
Pixel-Precise Explainable Stress Indexing: A Semantic Segmentation Framework for Disease Severity Quantification in Field Crops
Raunak Kumar, Soumyashree Kar
Plant diseases, resulting from both biotic and abiotic stresses, cause an estimated 20-40% loss in global agricultural yield annually, resulting in economic damages exceeding USD 2…
cs.GT2024
Learning in Budgeted Auctions with Spacing Objectives
Giannis Fikioris, Robert Kleinberg, Yoav Kolumbus +3
In many repeated auction settings, participants care not only about how frequently they win but also how their winnings are distributed over time. This problem arises in various pr…