In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Dodge等,2020. Fine-tuning pretrained language models: Weight initial
Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm. arXiv 2021, arXiv:2102.07350. [Google Scholar] Gu, Y.; Dong, L.; Wei, F.; Huang, M. Pre-Training to Learn in Context. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics ...
Prompts for Large Language Models generally have limited size, depending on the language model being used. Given that prompt-engine can persist dialog history, it is possible for dialogs to get so long that the prompt overflows. The Prompt Engine pattern handles this situation by removing the ol...
Methods of prompt programming Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm Language Models are Few-Shot Learners Large Language Models are Zero-Shot Reasoners Reasoning with Language Model Prompting: A Survey 编辑于 2023-03-06 22:00・江苏 ...
The Power of Scale for Parameter-Efficient Prompt Tuning (April 2021) Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm (Feb 2021) Calibrate Before Use: Improving Few-Shot Performance of Language Models (Feb 2021) Prefix-Tuning: Optimizing Continuous Prompts for Generation ...
Active Prompting with Chain-of-Thought for Large Language Models(opens in a new tab) (Feb 2023) More than you've asked for: A Comprehensive Analysis of Novel Prompt Injection Threats to Application-Integrated Large Language Models(opens in a new tab) (Feb 2023) ...
Vision-language artificial intelligence models (VLMs) possess medical knowledge and can be employed in healthcare in numerous ways, including as image interpreters, virtual scribes, and general decision support systems. However, here, we demonstrate that current VLMs applied to medical tasks exhibit ...
a new tab) (April 2021)The Power of Scale for Parameter-Efficient Prompt Tuning(opens in a new tab) (April 2021)Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm(opens in a new tab) (Feb 2021)Calibrate Before Use: Improving Few-Shot Performance of Language Models(...
A distinctive characteristic of modern Large Language Models is their few-shot and zero-shot [2] learning capability, meaning they can adapt to new tasks without the need for further training, simply through examples or textual instructions (prompts). This is made possible by their deep ...
Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm. Preprint. Laria Reynolds, Kyle McDonell. [pdf], 2021.2 Improving and Simplifying Pattern Exploiting Training. Preprint. Derek Tam, Rakesh R Menon, Mohit Bansal, Shashank Srivastava, Colin Raffel. [pdf], 2021.3 GPT unde...