Neural data-to-text generation with LM-based text augmentation
For many new application domains for data-to-text generation, the main obstacle in training
neural models consists of a lack of training data. While usually large numbers of instances …
neural models consists of a lack of training data. While usually large numbers of instances …
Diversifying dialogue generation with non-conversational text
Neural network-based sequence-to-sequence (seq2seq) models strongly suffer from the low-
diversity problem when it comes to open-domain dialogue generation. As bland and generic …
diversity problem when it comes to open-domain dialogue generation. As bland and generic …
Neural data-to-text generation via jointly learning the segmentation and correspondence
The neural attention model has achieved great success in data-to-text generation tasks.
Though usually excelling at producing fluent text, it suffers from the problem of information …
Though usually excelling at producing fluent text, it suffers from the problem of information …
Does the order of training samples matter? improving neural data-to-text generation with curriculum learning
Recent advancements in data-to-text generation largely take on the form of neural end-to-
end systems. Efforts have been dedicated to improving text generation systems by changing …
end systems. Efforts have been dedicated to improving text generation systems by changing …
Jointly improving language understanding and generation with quality-weighted weak supervision of automatic labeling
Neural natural language generation (NLG) and understanding (NLU) models are data-
hungry and require massive amounts of annotated data to be competitive. Recent …
hungry and require massive amounts of annotated data to be competitive. Recent …
Learning fine-grained fact-article correspondence in legal cases
Automatically recommending relevant law articles to a given legal case has attracted much
attention as it can greatly release human labor from searching over the large database of …
attention as it can greatly release human labor from searching over the large database of …
semipqa: A study on product question answering over semi-structured data
Product question answering (PQA) aims to automatically address customer questions to
improve their online shopping experience. Current research mainly focuses on finding …
improve their online shopping experience. Current research mainly focuses on finding …
Dart: A lightweight quality-suggestive data-to-text annotation tool
We present a lightweight annotation tool, the Data AnnotatoR Tool (DART), for the general
task of labeling structured data with textual descriptions. The tool is implemented as an …
task of labeling structured data with textual descriptions. The tool is implemented as an …
[PDF][PDF] Low-Resource Cross-Lingual Adaptive Training for Nigerian Pidgin
Developing effective spoken language processing systems for low-resource languages
poses several challenges due to the lack of parallel data and limited resources for fine …
poses several challenges due to the lack of parallel data and limited resources for fine …
Deep latent-variable models for text generation
X Shen - arXiv preprint arXiv:2203.02055, 2022 - arxiv.org
Text generation aims to produce human-like natural language output for down-stream tasks.
It covers a wide range of applications like machine translation, document summarization …
It covers a wide range of applications like machine translation, document summarization …