1. 在小样本的情况下,prompt-based tuning远远超过fine-tuning方法。当有足够训练数据时,fine-tuning模型也能够产生相当的结果。 2. ProtoVerb + ManualVerb方法结合时,能够产生更好的结果。 3. ProtoVerb+在untuned PLMs上仍然非常有效,证明了这种no-tuning method的有效性。 3. Analysis 3.1 Fixed Model Experim...
In this work, we introduce PTMGPT2, an interpretable protein language model that utilizes prompt-based fine-tuning to improve its accuracy in precisely predicting PTMs. Drawing inspiration from recent advancements in GPT-based architectures, PTMGPT2 adopts unsupervised learning to identify PTMs. It ...
[4] Fine-tune之后的NLP新范式:Prompt越来越火,CMU华人博士后出了篇综述文章 [5] 刘鹏飞:近代自然语言处理技术发展的“第四范式” [6] 必须要GPT3吗?不,BERT的MLM模型也能小样本学习 - 科学空间|Scientific Spaces [7] P-tuning:自动构建模版,释放语言模型潜能 - 科学空间|Scientific Spaces 以上为本文的全部...
In this paper, we reformulate the relation extraction task as mask language modeling and propose a novel adaptive prompt-based finetuning approach. We propose an adaptive label words selection mechanism that scatters the relation label into variable number of label tokens to handle the complex multip...
This is a paper list about prompt-based tuning for large-scale pre-trained language models. Different from traditional fine-tuning that uses an explicit classifier, prompt-based tuning directly uses the pre-trained models to conduct the pre-training tasks for classification or regression....
Chen X, Xie X, Zhang N, Yan J, Deng S, Tan C, Huang F, Si L, Chen H (2021) Adaprompt: adaptive prompt-based finetuning for relation extraction. arXiv preprint arXiv:2104.07650. Cui L, Wu Y, Liu J, Yang S, Zhang Y (2021) Template-based named entity recognition using BART. ...
We develop LinkPrompt , an adversarial attack algorithm to generate universal adversarial triggers (UATs) by a gradient-based beam search algorithm that not only effectively attacks the target pre-trained language models (PLMs) and prompt-based fine-tuning models (PFMs) but also maintains the natu...
Prompt-tuning提出很好的解决了pre-training和fine-tuning之间的gap,其根据设计的prompt实现下游任务的预测。目前人工构建的prompt成本较高; 三、方法 3.1 任务描述 ,三个sub-task的输出分别表示为: 本文提出模型如下图: 其主要包括两个部分: SentiPrompt tuning:在给定输入句子以及aspect以及opinion的前提下,设计continu...
This paper proposes a novel fine-tuning strategy for adapting a pretrained transformer-based segmentation model on data from a new medical center. This method introduces a small number of learnable parameters, termed prompts, into the input space (less than 1% of model parameters) while keeping ...
(Brown et al. 2020) which does not require gradient-based fine-tuning but instead uses a few examples in the LM context as the only source of learning. In this paper, we explore prompt-based few-shot learning in dialogue tasks. We benchmark LMs of different sizes in nine response ...