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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 31–40 of 43 papers

TitleStatusHype
Coordination Generation via Synchronized Text-Infilling—0
Decoding As Dynamic Programming For Recurrent Autoregressive Models—0
Don't Prompt, Search! Mining-based Zero-Shot Learning with Language Models—0
Enhancing Spoken Discourse Modeling in Language Models Using Gestural Cues—0
Flexible-length Text Infilling for Discrete Diffusion Models—0
Generative Prompt Tuning for Relation Classification—0
InFillmore: Frame-Guided Language Generation with Bidirectional Context—0
"Mask and Infill" : Applying Masked Language Model to Sentiment Transfer—0
Nutri-bullets Hybrid: Consensual Multi-document Summarization—0
On the Role of Bidirectionality in Language Model Pre-Training—0
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