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Text Infilling

Text Infilling is the task of predicting missing spans of text which are consistent with the preceding and subsequent text. Text Infilling is a generalization of the cloze task—cloze historically refers to infilling individual words.

Source: Enabling Language Models to Fill in the Blanks

Papers

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Showing 21–30 of 43 papers

TitleStatusHype
Towards Probabilistically-Sound Beam Search with Masked Language ModelsCode0
Keep Calm and Switch On! Preserving Sentiment and Fluency in Semantic Text ExchangeCode0
Empowering Character-level Text Infilling by Eliminating Sub-TokensCode0
Conformal prediction for text infilling and part-of-speech predictionCode0
TIGS: An Inference Algorithm for Text Infilling with Gradient SearchCode0
Insertion Language Models: Sequence Generation with Arbitrary-Position Insertions—0
A Benchmark for Text Expansion: Datasets, Metrics, and Baselines—0
A-TIP: Attribute-aware Text Infilling via Pre-trained Language Model—0
BiTIIMT: A Bilingual Text-infilling Method for Interactive Machine Translation—0
Building a Knowledge-Based Dialogue System with Text Infilling—0
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