Prompt Engineering
هندسة التحفيز
فن وعلم تصميم المدخلات النصية التي تُعطى للنماذج اللغوية الكبيرة لتوجيه سلوكها نحو المخرجات المطلوبة، دون تعديل معاملات النموذج.
The art and science of designing text inputs given to large language models to steer their behavior toward desired outputs, without modifying model parameters.
Also translated asتصميم المُحفِّزات، تصميم المُوجِّهات، صياغة الأوامر النصية، صياغة وهندسة المحثّات، هندسة الأوامر النصية، هندسة الحوافز النصية، هندسة الحَثّ
First appears in this corpus in: A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence (1956)
Appears in these papers
- Learning Transferable Visual Models from Natural Language Supervision2021in the sky ✦
- Learning Transferable Visual Models from Natural Language Supervision2021in the sky ✦
- A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence1956in the sky ✦
- Emergent Abilities of Large Language Models2022in the sky ✦
- Improving Language Understanding by Generative Pre-Training2018in the sky ✦
- Language Models Are Unsupervised Multitask Learners2019in the sky ✦
- Language Models Are Few-Shot Learners2020in the sky ✦
- Language Models Are Few-Shot Learners2020in the sky ✦
- HuggingGPT: Solving AI Tasks with ChatGPT and Its Friends in Hugging Face2023in the sky ✦
- HyDE: Precise Zero-Shot Dense Retrieval without Relevance Labels2022in the sky ✦
- Learning to Reason with LLMs2024in the sky ✦
- The Power of Scale for Parameter-Efficient Prompt Tuning2021in the sky ✦
- Do As I Can, Not As I Say: Grounding Language in Robotic Affordances2022in the sky ✦
- Do As I Can, Not As I Say: Grounding Language in Robotic Affordances2022in the sky ✦
- Sparks of Artificial General Intelligence: Early Experiments with GPT-42023in the sky ✦
- Voyager: An Open-Ended Embodied Agent with Large Language Models2023in the sky ✦