Felix: Flexible Text Editing Through Tagging and Insertion

• URL: http://arxiv.org/abs/2003.10687v1
• Date: Tue, 24 Mar 2020 07:01:09 GMT
• Title: Felix: Flexible Text Editing Through Tagging and Insertion
• Authors: Jonathan Mallinson, Aliaksei Severyn, Eric Malmi, Guillermo Garrido
• Abstract summary: Felix is a flexible text-editing approach for generation, designed to derive the maximum benefit from the ideas of decoding with bi-directional contexts and self-supervised pre-training. We achieve this by decomposing the text-editing task into two sub-tasks: tagging to decide on the subset of input tokens and their order in the output text and insertion to in-fill the missing tokens in the output not present in the input.
• Score: 21.55417495142206
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present Felix --- a flexible text-editing approach for generation, designed to derive the maximum benefit from the ideas of decoding with bi-directional contexts and self-supervised pre-training. In contrast to conventional sequence-to-sequence (seq2seq) models, Felix is efficient in low-resource settings and fast at inference time, while being capable of modeling flexible input-output transformations. We achieve this by decomposing the text-editing task into two sub-tasks: tagging to decide on the subset of input tokens and their order in the output text and insertion to in-fill the missing tokens in the output not present in the input. The tagging model employs a novel Pointer mechanism, while the insertion model is based on a Masked Language Model. Both of these models are chosen to be non-autoregressive to guarantee faster inference. Felix performs favourably when compared to recent text-editing methods and strong seq2seq baselines when evaluated on four NLG tasks: Sentence Fusion, Machine Translation Automatic Post-Editing, Summarization, and Text Simplification.

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