text representation: 使text形成计算机更易计算/理解的方式:Bag-of-words (BOW), N-gram, term frequency-inverse document frequency (TF-IDF), word2vec and GloVe BOW: representing each text with a dictionary-sized vector 缺点:cannot properly capture more complex linguistic phenomena in sentiment analy...
1.Word Representation Learning 作者提出将单词的左上下文、右上下文、单词本身结合起来作为单词表示。作者使用了双向RNN来分别提取句子的上下文信息。公式如下。 其中, cl (wi)代表单词wi的左上下文,cl (wi)由上一个单词的左上下文cl (wi−1)和上一个单词的词嵌入向量e (wi−1)计算得到,如公式(1)所示,所有...
三个句子拼接起来，送入一个自行微调过（fine-tuned）的BERT，获得一个representation用于sim(·, ·)的...
当GNN遇见NLP(五) Sentence-State LSTM for Text Representation,ACL2018,程序员大本营,技术文章内容聚合第一站。
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance 来自 掌桥科研 喜欢 0 阅读量: 248 作者:P Cheng,MR Min,D Shen,C Malon,Y Zhang,Y Li,L Carin 摘要: Learning disentangled representations of natural language is essential for many NLP tasks, e.g., conditional ...
数据集构建:将原生的 text2SQL 数据处理成合适的格式(Text Representation Format)以微调 LLM。这包括将问题和数据库 schema 的描述集成到提示中作为指令(instruction),以及各种问题表示以提高训练和评估期间的性能。此外,将选择不同的 few-shot 策略(例如 example selection 和 organization)来构建评估数据集 ...
When we say “good” dataset, we mean a dataset that is a true representation of the data we’re likely to see in production. Throughout this chapter, we’ll use some of the publicly available datasets for text classification. A wide range of NLP-related datasets, including ones for text...
Text classification is a fundamental task in NLP applications. Most existing work relied on either explicit or implicit text representation to address this problem. While these techniques work well for sentences, they can not easily be a... W Jin,Z Wang,D Zhang,... 被引量: 8发表: 2017年...
我个人感觉这个Proximity概念挺好的,但是感觉运算定义有点太粗暴了,三个句子拼接起来,送入一个自行微调过(fine-tuned)的BERT,获得一个representation用于sim(·, ·)的计算 对于Multi-Doc设定下的Centrality(Eq. 8),个人感觉还是挺爽朗的。其既考虑了同一文内句子的影响力,也考虑了文外句子的影响,并设置成一种可控...
Three types of feature representation in NLP Depending on the specific task or model you’re dealing with, one or more of these feature types in the Venn diagram may be particularly important to your model’s performance — for example, word embeddings accompanied by some subset of custom lingu...