Unleash GPT-2 power for event detection
Event Detection (ED) aims to recognize mentions of events (ie, event triggers) and their
types in text. Recently, several ED datasets in various domains have been proposed …
types in text. Recently, several ED datasets in various domains have been proposed …
Label-specific feature augmentation for long-tailed multi-label text classification
Multi-label text classification (MLTC) involves tagging a document with its most relevant
subset of labels from a label set. In real applications, labels usually follow a long-tailed …
subset of labels from a label set. In real applications, labels usually follow a long-tailed …
[PDF][PDF] 标签推荐方法研究综述
徐鹏宇， 刘华锋， 刘冰， 景丽萍， 于剑 - 软件学报, 2021 - jos.org.cn
随着互联网信息的爆炸式增长, 标签(由用户指定用来描述项目的关键词) 在互联网信息检索领域
中变得越来越重要. 为在线内容赋予合适的标签, 有利于更高效的内容组织和内容消费 …
中变得越来越重要. 为在线内容赋予合适的标签, 有利于更高效的内容组织和内容消费 …
A survey of methods for addressing class imbalance in deep-learning based natural language processing
Many natural language processing (NLP) tasks are naturally imbalanced, as some target
categories occur much more frequently than others in the real world. In such scenarios …
categories occur much more frequently than others in the real world. In such scenarios …
Guiding generative language models for data augmentation in few-shot text classification
Data augmentation techniques are widely used for enhancing the performance of machine
learning models by tackling class imbalance issues and data sparsity. State-of-the-art …
learning models by tackling class imbalance issues and data sparsity. State-of-the-art …
Queaco: Borrowing treasures from weakly-labeled behavior data for query attribute value extraction
We study the problem of query attribute value extraction, which aims to identify named
entities from user queries as diverse surface form attribute values and afterward transform …
entities from user queries as diverse surface form attribute values and afterward transform …
Improving Dutch vaccine hesitancy monitoring via multi-label data augmentation with GPT-3.5
J Van Nooten, W Daelemans - Proceedings of the 13th …, 2023 - repository.uantwerpen.be
In this paper, we leverage the GPT-3.5 language model both using the Chat-GPT API
interface and the GPT-3.5 API interface to generate realistic examples of anti-vaccination …
interface and the GPT-3.5 API interface to generate realistic examples of anti-vaccination …
Textual data augmentation for patient outcomes prediction
Deep learning models have demonstrated superior performance in various healthcare
applications. However, the major limitation of these deep models is usually the lack of high …
applications. However, the major limitation of these deep models is usually the lack of high …
Augmenting open-domain event detection with synthetic data from gpt-2
Open-domain event detection (ODED) aims to identify event mentions of all possible types in
text. A challenge for ODED research is the lack of large training datasets. In this work, we …
text. A challenge for ODED research is the lack of large training datasets. In this work, we …
Generating labeled data for relation extraction: A meta learning approach with joint GPT-2 training
Relation Extraction (RE) is the task of identifying semantic relation between real-world
entities mentioned in text. Despite significant progress in RE research, a remaining …
entities mentioned in text. Despite significant progress in RE research, a remaining …