Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
Beyond Aggregate Accuracy: Item-Level Transitions in Prompt Optimization
Chinmoy Mitra, Tarek Mahmud
Automatic prompt optimization (APO) uses feedback from model responses to improve prompts automatically. However, its effectiveness is usually measured through overall scores, whic…
cs.LG2026
Personalized Fall Detection by Balancing Data with Selective Feedback Using Contrastive Learning
Awatif Yasmin, Tarek Mahmud, Sana Alamgeer +1
Personalized fall detection models can significantly improve accuracy by adapting to individual motion patterns, yet their effectiveness is often limited by the scarcity of real-wo…