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Found 9 papers, 1 papers with code
``Judge me by my size (noun), do you?'' YodaLib: A Demographic-Aware Humor Generation Framework
The subjective nature of humor makes computerized humor generation a challenging task.
SemEval-2020 Task 7: Assessing Humor in Edited News Headlines
The second subtask is to predict, for a pair of edited versions of the same original headline, which is the funnier version.
Simple and Effective Retrieve-Edit-Rerank Text Generation
Retrieve-and-edit seq2seq methods typically retrieve an output from the training set and learn a model to edit it to produce the final output.
"Judge me by my size (noun), do you?'' YodaLib: A Demographic-Aware Humor Generation Framework
The subjective nature of humor makes computerized humor generation a challenging task.
Stimulating Creativity with FunLines: A Case Study of Humor Generation in Headlines
Building datasets of creative text, such as humor, is quite challenging.
``President Vows to Cut \textlessTaxes\textgreater Hair'': Dataset and Analysis of Creative Text Editing for Humorous Headlines
We introduce, release, and analyze a new dataset, called Humicroedit, for research in computational humor.
"President Vows to Cut <Taxes> Hair": Dataset and Analysis of Creative Text Editing for Humorous Headlines
We introduce, release, and analyze a new dataset, called Humicroedit, for research in computational humor.
Filling the Blanks (hint: plural noun) for Mad Libs Humor
Computerized generation of humor is a notoriously difficult AI problem.
Inferring Fine-grained Details on User Activities and Home Location from Social Media: Detecting Drinking-While-Tweeting Patterns in Communities
Nearly all previous work on geo-locating latent states and activities from social media confounds general discussions about activities, self-reports of users participating in those activities at times in the past or future, and self-reports made at the immediate time and place the activity occurs.
