Table-to-text Generation by Structure-aware Seq2seq Learning Accepted by AAAI2018 【摘要】 传统Sequence to Sequence是采用端到端的方式处理由句子X生成句子Y的通用模型框架,但是当数据来自于多源纬度不同的信息时,传统Encoder-Decoder框架技术缺乏能够融合多源属性并生成更为一致的描述内容的整体归纳能力。为此,我...
在“ ToTTo: A Controlled Table-To-Text Generation Dataset ”中,我们展示了一个开放域表到文本生成数据集,该数据集使用一种新颖的注释过程(通过句子修订)以及一个受控文本生成任务来创建,该任务可用于评估模型幻觉。ToTTo(“Table-To-Text”的简写)包含 121,000 个训练示例,以及每个用于开发和测试的 7,500 个...
Liu, T., Wang, K., Sha, L., Chang, B., & Sui, Z. (2018). Table-to-text generation by structure-aware seq2seq learning. 32nd AAAI Conference on Artificial Intelligence, AAAI 2018, 4881–4888.https://arxiv.org/pdf/1711.09724.pdf https://github.com/tyliupku/wiki2bio 注意数据格式...
2018. Table-to-text Generation by Structure-aware Seq2seq Learning. In Associ- ation for the Advancement of Artificial Intelligence (AAAI).Liu et al. 2018] Liu, T.; Wang, K.; Sha, L.; Chang, B.; and Sui, Z. 2018. Table-to-text generation by structure-aware seq2seq learning....
Table-to-text generation aims to generate a description for a factual table which can be viewed as a set of field-value records. To encode both the content and the structure of a table, we propose a novel structure-aware seq2seq architecture which consists of field-gating encoder and descri...
原文地址 介绍 数据到文本的生成方法指的是从非文本的输入中生成描述性文本的任务。输入种类不同,任务可以定义地更加明确,比如摘要信息生成文本,信息框生成文本,图生成文本。 在这些任务中,我们关注逻辑表到文本的生成任务,这项任务旨在从表格生成流畅的但是逻辑正确
Neural table-to-text generation approaches are data-hungry, limiting their adaptation for low-resource real-world applications. Previous works mostly resort to Pre-trained Language Models (PLMs) to generate fluent summaries of a table. However, they often contain hallucinated contents due to the ...
Generating fluent, coherent, and informative text from structured data is called table-to-text generation. Copying words from the table is a common method to solve the “out-of-vocabulary” problem, but it’s difficult to achieve accurate copying. In order to overcome this problem, we invent ...
Table-to-text generation involves generating appropriate textual descriptions given structured tabular data. It has attracted increasing attention in recent years thanks to the popularity of neural network models and the availability of large-scale datasets. A common feature across existing methods is ...
Generating fluent, coherent, and informative text from structured data is called table-to-text generation. Copying words from the table is a common method to solve the "out-of-vocabulary" problem, but it's difficult to achieve accurate copying. In order to overcome this problem, we invent an...