From Simulation to Experiment: Benchmarking Machine-Learning Models for Quantum-Dot State Recognition

arXiv:2511.22451 · cs.CV, cond-mat.mes-hall, cs.LG · Submitted 2025-11-27 · Read on arXiv

cs.CV, cond-mat.mes-hall, cs.LG

Submitted: 2025-11-27

Updated: 2026-10-24

Terminology

• Accuracy — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 4 episodes
• Calibration — 1× in this paper · explained in 9 episodes
• Machine Learning (ML) — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformers — 1× in this paper · explained in 2 episodes

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models