Tag: few-shot learning
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Robust Data-Free Meta-Learning Against Task Shifts
Explore a robust framework for data-free meta-learning that tackles task-distribution shifts and model corruption for reliable few-shot learning.
Few-Shot Writer Adaptation for Handwritten Text Recognition
Discover few-shot writer adaptation via multimodal in-context learning to improve handwritten text recognition without complex updates or tuning.
Uni-DAD: Fast Few-Shot Image Generation with Diffusion Models
Uni-DAD unifies distillation and adaptation in diffusion models for rapid, high-quality few-shot image generation with improved diversity and stability.
Few-Shot Learning in Language Models: Key Insights
Discover how language models use few-shot learning to adapt quickly with minimal data, transforming AI applications in NLP and beyond.