4 citations
3 papers
cs.CL2026
LLM-based Atomic Propositions help weak extractors: Evaluation of a Propositioner for triplet extraction
Luc Pommeret, Thomas Gerald, Patrick Paroubek +3
Knowledge Graph construction from natural language requires extracting structured triplets from complex, information-dense sentences. In this paper, we investigate if the decomposi…
cs.CV2025★ 4 cited
Anomaly-Aware YOLO: A Frugal yet Robust Approach to Infrared Small Target Detection
Alina Ciocarlan, Sylvie Le Hégarat-Mascle, Sidonie Lefebvre
Infrared Small Target Detection (IRSTD) is a challenging task in defense applications, where complex backgrounds and tiny target sizes often result in numerous false alarms using c…
cs.CV2024
Self-Supervised Learning for Real-World Object Detection: a Survey
Alina Ciocarlan, Sidonie Lefebvre, Sylvie Le Hégarat-Mascle +1
Self-Supervised Learning (SSL) has emerged as a promising approach in computer vision, enabling networks to learn meaningful representations from large unlabeled datasets. SSL meth…