Few-Shot Prompting

التحفيز بأمثلة قليلة

أسلوب يُعطى فيه النموذج اللغوي عدداً صغيراً من أمثلة الإدخال والإخراج ضمن التحفيز لتوجيه سلوكه على مهام جديدة، بدون أي تحديث لمعاملاته.

A technique where a language model is given a small number of input-output examples in its prompt to guide its behavior on new tasks, without any parameter updates.

Also translated asالاستنطاق بأمثلة قليلة، التحفيز بعدد محدود من الأمثلة، التحفيز بعيّنات محدودة، التعلم بأمثلة قليلة عبر التحفيز، التلقين بأمثلة محدودة، التوجيه بأمثلة قليلة

First appears in this corpus in: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (2022)

Appears in these papers

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models2022 in the sky ✦
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models2022 in the sky ✦
Emergent Abilities of Large Language Models2022 in the sky ✦
Emergent Abilities of Large Language Models2022 in the sky ✦
HuggingGPT: Solving AI Tasks with ChatGPT and Its Friends in Hugging Face2023 in the sky ✦
PaLM: Scaling Language Modeling with Pathways2022 in the sky ✦
ReAct: Synergizing Reasoning and Acting in Language Models2023 in the sky ✦
ReAct: Synergizing Reasoning and Acting in Language Models2023 in the sky ✦
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback2023 in the sky ✦
Self-Consistency Improves Chain of Thought Reasoning in Language Models2022 in the sky ✦
Self-Instruct: Aligning Language Models with Self-Generated Instructions2022 in the sky ✦
WebArena: A Realistic Web Environment for Building Autonomous Agents2023 in the sky ✦
WebArena: A Realistic Web Environment for Building Autonomous Agents2023 in the sky ✦