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Found 12 papers, 3 papers with code
GLUCOSE: GeneraLized and COntextualized Story Explanations
As a step toward AI systems that can build similar mental models, we introduce GLUCOSE, a large-scale dataset of implicit commonsense causal knowledge, encoded as causal mini-theories about the world, each grounded in a narrative context.
Tackling the Story Ending Biases in The Story Cloze Test
The Story Cloze Test (SCT) is a recent framework for evaluating story comprehension and script learning.
LSDSem 2017 Shared Task: The Story Cloze Test
The LSDSem{'}17 shared task is the Story Cloze Test, a new evaluation for story understanding and script learning.
Image-Grounded Conversations: Multimodal Context for Natural Question and Response Generation
The popularity of image sharing on social media and the engagement it creates between users reflects the important role that visual context plays in everyday conversations.
Visual Storytelling
We introduce the first dataset for sequential vision-to-language, and explore how this data may be used for the task of visual storytelling.
A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories
We created a new corpus of ~50k five-sentence commonsense stories, ROCStories, to enable this evaluation.
Generating Natural Questions About an Image
There has been an explosion of work in the vision & language community during the past few years from image captioning to video transcription, and answering questions about images.
A Survey of Current Datasets for Vision and Language Research
Integrating vision and language has long been a dream in work on artificial intelligence (AI).
