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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

Showing 110 of 43 papers

TitleStatusHype
LaViDa: A Large Diffusion Language Model for Multimodal UnderstandingCode3
The Devil behind the mask: An emergent safety vulnerability of Diffusion LLMsCode2
A Simple yet Effective Framework for Few-Shot Aspect-Based Sentiment AnalysisCode1
Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense ReasoningCode1
Enabling Language Models to Fill in the BlanksCode1
Language modeling via stochastic processesCode1
Having Beer after Prayer? Measuring Cultural Bias in Large Language ModelsCode1
Generative Prompt Tuning for Relation ClassificationCode1
CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text GenerationCode1
Improving Sequence-to-Sequence Pre-training via Sequence Span RewritingCode1
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