WebApr 12, 2024 · Here are some ChatGPT prompts that you can use to create engaging email marketing campaigns: Email s ubject line optimization: Use ChatGPT to generate ideas for compelling subject lines that grab your audience’s attention and entice them to open your emails. A/B testing: Use ChatGPT to create different versions of your email content and … WebDec 19, 2024 · Experiments show that PromptBoosting achieves state-of-the-art performance in multiple black-box few-shot classification tasks, and matches or outperforms full fine-tuning in both few-shot and standard learning paradigms, while training 10x faster than existing black-box methods. Score: 61.38341243907045

PromptBoosting: Black-Box Text Classification with Ten …

WebJan 28, 2024 · Instead of directly optimizing in prompt space, PromptBoosting obtains a small pool of prompts via a gradient-free approach and then constructs a large pool of weak learners by pairing these prompts with different elements of the LM's output distribution. Language Modelling text-classification +1 3 Paper Code WebWe describe PromptBoosting, a query-efficient procedure for building a text classifier from a neural language model (LM) without access to the LM's parameters, gradients, or hidden representations. This form of "black-box" classifier training has become increasingly important as the cost of training and inference in large-scale LMs grows. But existing … marks and spencer feedback survey

[PDF] PromptBoosting: Black-Box Text Classification with …

WebAug 28, 2024 · 「Prompt Tuning也许会是深度学习时代的Feature Engineering问题，如何给各大任务设计合理的Prompts将会是很有意思的科学问题」–刘知远虽然博主以前也看到了基于 Prompt-tuning 让GPT-3处理各种类型的任务，直接处理零样本和小样本学习能力。也整理过GPT，OpenAI CLIP，DALL-E 这些文章。 WebPromptBoosting: Black-Box Text Classification with Ten Forward Passes. B Hou, J O'Connor, J Andreas, S Chang, Y Zhang. arXiv preprint arXiv:2212.09257, 2024. 2024: TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization. B Hou, J Jia, Y Zhang, G Zhang, Y Zhang, S Liu, S Chang. WebPromptBoosting: Black-Box Text Classification with Ten Forward Passes (hou, …, jacob andreas, …, zhang, 2024) - get a small pool of prompts, learn a verbalizer (final classification layer) for each, then ensemble them with AdaBoost on LLM output. people have studied many works on prompt ensembling (e.g. lester et al. 2024) marks and spencer feedback