Few-Shot Learning

Few-shot learning research is predominantly evaluated on accuracy alone, with limited attention to the parameter and training-sample budgets required to reach that accuracy - a real constraint for practitioners without l…

Few-Shot Image Classification Few-Shot Learning

Enhancing Accessibility of Medical Texts through Large Language Model-Driven Plain Language Adaptation

2026-09-15 · Ting-Wei Chang, Hen-Hsen Huang, Hsin-Hsi Chen arxiv

This paper addresses the challenge of making complex healthcare information more accessible through automated Plain Language Adaptation (PLA). PLA aims to simplify technical medical language, bridging a critical gap betw…

Reading Comprehension Text Simplification Few-Shot Learning

Sample-Conditioned Representation Selection for Audio Few-Shot Learning

2026-09-15 · Fengrui Liu, Ningxin Shen, Yi Li, Yiwei Fu 외 arxiv

Few-shot audio classifiers may rely on foreground-background co-occurrences and fail when those correlations shift. On SpurAudio, the resulting representation shift is concentrated and class dependent: for ResNet12, the …

Few-Shot Learning

Learning to Adapt and Calibrate: Score Distribution Alignment for Few-Shot Uncertainty Prediction in Medical VLMs

2026-09-09 · Xuan Cuong Ngo, Ngan Le arxiv

Uncertainty estimation for medical vision--language models (VLMs) using conformal prediction has gained increasing attention due to its distribution-free coverage guarantees. However, standard conformal prediction relies…

Few-Shot Learning

Decoupled I/O-Dominant Pipelines for Large-Scale Whole-Slide Image Embedding Extraction

2026-08-27 · Mayanka Chandrashekar, Xi Zhang, Ethan Seefried, Tirthankar Ghosal 외 arxiv

Whole-slide images (WSIs) are central to computational pathology but are prohibitively large, making patch-based processing the practical unit for foundation model inference. At scale, however, generating and handling ma…

Few-Shot Learning

MetaCaster: Meta-Harness-Optimized Agent for End-to-End Few-Shot Learning of Lightweight Time Series Forecasters

2026-08-24 · ChengAo Shen, Wenchao Yu, Fangyu Wu, Dongjin Song 외 arxiv

Time series forecasting (TSF) is evolving toward multimodal and agentic settings, yet using foundation models remains uneconomical in resource-constrained scenarios, where compact, specialized forecasters are more desira…

Computational Efficiency Time Series Forecasting Few-Shot Learning

전체 3,293편 보기 →