Few-Shot Learning
التعلّم بأمثلة قليلة
قدرة النموذج على أداء مهمة بمجرد تقديم حفنة من الأمثلة التوضيحية في سياق المدخلات دون تحديث أوزانه.
The ability of a model to perform a task given only a handful of examples provided in the input context, without updating its weights.
Also translated asالاكتساب المعرفي من شواهد قليلة، التدريب فائق السرعة بمدخلات محدودة، التعلم القليل العيّنات، التعلم بعيّنات محدودة
First appears in this corpus in: Improving Language Understanding by Generative Pre-Training (2018)
Appears in these papers
- Atlas: Few-shot Learning with Retrieval Augmented Language Models2023in the sky ✦
- Atlas: Few-shot Learning with Retrieval Augmented Language Models2023in the sky ✦
- Emergent Abilities of Large Language Models2022in the sky ✦
- Flamingo: a Visual Language Model for Few-Shot Learning2022in the sky ✦
- Flamingo: a Visual Language Model for Few-Shot Learning2022in the sky ✦
- Finetuned Language Models Are Zero-Shot Learners2022in the sky ✦
- Finetuned Language Models Are Zero-Shot Learners2022in the sky ✦
- Scaling Language Models: Methods, Analysis & Insights from Training Gopher2022in the sky ✦
- Improving Language Understanding by Generative Pre-Training2018in the sky ✦
- Language Models Are Few-Shot Learners2020in the sky ✦
- GPT-4 Technical Report2023in the sky ✦
- ImageBind: One Embedding Space to Bind Them All2023in the sky ✦
- ImageBind: One Embedding Space to Bind Them All2023in the sky ✦
- OPT: Open Pre-Trained Transformer Language Models2022in the sky ✦
- OPT: Open Pre-Trained Transformer Language Models2022in the sky ✦
- PaLM: Scaling Language Modeling with Pathways2022in the sky ✦
- PaLM: Scaling Language Modeling with Pathways2022in the sky ✦
- Sparks of Artificial General Intelligence: Early Experiments with GPT-42023in the sky ✦
- STaR: Bootstrapping Reasoning With Reasoning2022in the sky ✦