Fetching the paper…
Reading the bibliography…
Wit is a form of rich interaction that is often grounded in a specific situation (e.g., a comment in response to an event).
A two-stage model for the appreciation of jokes and cartoons: An information-processing analysis
Jerry M Suls. 1972 · 1972
Earlier work this paper cites.
Language of riddles: new perspectives
William J Pepicello and Thomas A Green. 1984 · 1984
Earlier work this paper cites.
Imperfect puns, markedness, and phonological similarity: With fronds like these, who needs anemones
Arnold Zwicky and Elizabeth Zwicky. 1986 · 1986
Earlier work this paper cites.
Script theory revis (it) ed: Joke similarity and joke representation model
Salvatore Attardo and Victor Raskin. 1991 · 1991
Earlier work this paper cites.
Machine humour: An implemented model of puns
Kim Binsted. 1996 · 1996
Earlier work this paper cites.
Computational rules for generating punning riddles
Kim Binsted and Graeme Ritchie. 1997 · 1997
Earlier work this paper cites.
Nltk: The natural language toolkit
Edward Loper and Steven Bird. 2002 · 2002
Earlier work this paper cites.
HAHAcronym: A computational humor system
Oliviero Stock and Carlo Strapparava. 2005 · 2005
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009 · 2009
Earlier work this paper cites.
The funny thing about incongruity: A computational model of humor in puns
Justine T Kao, Roger Levy, and Noah D Goodman. 2013 · 2013
Cited alongside, same era.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
Cited alongside, same era.
Unsupervised joke generation from big data
Sasa Petrovic and David Matthews. 2013 · 2013
Cited alongside, same era.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
Cited alongside, same era.
Revisiting word neighborhoods for speech recognition
Preethi Jyothi and Karen Livescu. 2014 · 2014
Cited alongside, same era.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014 · 2014
Show and tell: Lessons learned from the 2015 mscoco image captioning challenge
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan. 2016 · 2015
Later among the works it cites.
I can has cheezburger? a nonparanormal approach to combining textual and visual information for predicting and generating popular meme descriptions
William Yang Wang and Miaomiao Wen. 2015 · 2015
Later among the works it cites.
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
Later among the works it cites.
We are humor beings: Understanding and predicting visual humor
Arjun Chandrasekaran, Ashwin Kalyan, Stanislaw Antol, Mohit Bansal, Dhruv Batra, C. Lawrence Zitnick, and Devi Parikh. 2016 · 2016
Later among the works it cites.
Generating topical poetry
Marjan Ghazvininejad, Xing Shi, Yejin Choi, and Kevin Knight. 2016 · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Unifying visual-semantic embeddings with multimodal neural language models
Ryan Kiros, Ruslan Salakhutdinov, and Richard S Zemel. 2014 · 2014
Cited alongside, same era.
Dragomir Radev, Amanda Stent, Joel Tetreault, Aasish Pappu, Aikaterini Iliakopoulou, Agustin Chanfreau, Paloma de Juan, Jordi Vallmitjana, Alejandro Jaimes, Rahul Jha, et al. 2015 · 2015
Cited alongside, same era.
Inside jokes: Identifying humorous cartoon captions
Dafna Shahaf, Eric Horvitz, and Robert Mankoff. 2015 · 2015
Cited alongside, same era.
Phonological pun-derstanding
Aaron Jaech, Rik Koncel-Kedziorski, and Mari Ostendorf. 2016 · 2016
Later among the works it cites.
A wizard-of-oz study on a non-task-oriented dialog systems that reacts to user engagement
Zhou Yu, Leah Nicolich-Henkin, Alan W Black, and Alex I Rudnicky. 2016 · 2016
Later among the works it cites.
Exploring the limits of language modeling
Rafal Jozefowicz, Oriol Vinyals, Mike Schuster, Noam Shazeer, and Yonghui Wu. 2016 · 2016
Later among the works it cites.
Inception-v4, inception-resnet and the impact of residual connections on learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi. 2017 · 2017
Closest in time.