skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • Home
  • Search Results
  • Page 1 of 1

Search for: All records

Creators/Authors contains: "Ye, Keren"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. ; (, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW))
    Full Text Available 
  2. ; ; ; ; ; ; ; (, IEEE Transactions on Pattern Analysis and Machine Intelligence)
    Full Text Available 
  3. ; (, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR))
    null (Ed.)
    Accepted Manuscript Full Text Available
  4. ; (, Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI))
    null (Ed.)
    Accepted Manuscript Full Text Available
  5. ; ; (, Proceedings of the Winter Conference on Applications of Computer Vision (WACV))
    null (Ed.)
    Full Text Available 
  6. ; ; ; (, The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020)
    Growing up with bedtime tales, even children could easily tell how a story should develop; but selecting a coherent and reasonable ending for a story is still not easy for machines. To successfully choose an ending requires not only detailed analysis of the context, but also applying commonsense reasoning and basic knowledge. Previous work has shown that language models trained on very large corpora could capture common sense in an implicit and hard-to-interpret way. We explore another direction and present a novel method that explicitly incorporates commonsense knowledge from a structured dataset, and demonstrate the potential for improving story completion. 
    more » « less
    Full Text Available