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- W2963549533 abstract "Wit is a form of rich interaction that is often grounded in a specific situation (e.g., a comment in response to an event). In this work, we attempt to build computational models that can produce witty descriptions for a given image. Inspired by a cognitive account of humor appreciation, we employ linguistic wordplay, specifically puns, in image descriptions. We develop two approaches which involve retrieving witty descriptions for a given image from a large corpus of sentences, or generating them via an encoder-decoder neural network architecture. We compare our approach against meaningful baseline approaches via human studies and show substantial improvements. Moreover, in a Turing test style evaluation, people find the image descriptions generated by our model to be slightly wittier than human-written witty descriptions when the human is subject to similar constraints as the model regarding word usage and style." @default.
- W2963549533 created "2019-07-30" @default.
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- W2963549533 date "2018-01-01" @default.
- W2963549533 modified "2023-09-28" @default.
- W2963549533 title "Punny Captions: Witty Wordplay in Image Descriptions" @default.
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- W2963549533 doi "https://doi.org/10.18653/v1/n18-2121" @default.
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