Christopher Berner, Christopher M. Hesse, Sam McCandlish, Alec Radford, Ilya Sutskever. This paper explores methods for creating and using controlled datasets for MLM, and provides a practical guide for implementing the task.
在自然语言处理领域，基于掩码语言模型(Masked Language Model)的代理任务，BERT成功引领了自监督预训练的...
The proposed method involves two learning tasks: valence–arousal intensity estimation, which is the major task, and random masked sentiment word prediction, which is the auxiliary task modify from mask language modeling, used to enhance the model performance. The experimental results indicate that ...
给定节点,,它们的重叠子图大小为,设重叠子图中最大规模为;此外,图中节点的特征都是独立同分布地随机采样自一个的高斯分布,则我们可以给出 task irrelevant 信息的一个下界: 这个下界说明 task irrelevant 的信息和给定两点之间的 k-hop 邻域的重叠程度是正相关的,因此当我们采取基于边的掩码策略时,可以有效地去除 ...
Unified vision-language frameworks have greatly advanced in recent years, most of which adopt an encoder-decoder architecture to unify image-text tasks as sequence-to-sequence generation. However, existing video-language (VidL) models still require task-specific designs in ...
Say I want to train a model for sequence classification. And so I define my model to be: model = DistilBertForSequenceClassification.from_pretrained("bert-base-uncased") My question is - what would be the optimal way if I want to pre-train this model with masked langu...
MPNet can see full position information and know there are two tokens to predict, and thus it can model the dependency among predicted tokens and predict the tokens better. ObjectiveFactorization MLM (BERT) log P (sentence | the task is [M] [M]) + log P (clas...
Masked Sentence Model Based on BERT for Move Recognition in Medical Scientific Abstracts Purpose: Move recognition in scientific abstracts is an NLP task of classifying sentences of the abstracts into different types of language units. To impro... G Yu,Z Zhang,H Liu,... - 《数据与情报科学学报...
In theory, our model is able to infer all tokens and gen- erate the entire image in a single pass. We find this chal- lenging due to inconsistency with the training task. Below, the proposed iterative decoding is introduced. To generate an image at inference time, we start from a ...
MPNet can see full position information and know there are two tokens to predict, and thus it can model the dependency among predicted tokens and predict the tokens better. ObjectiveFactorization MLM (BERT) log P (sentence | the task is [M] [M]...