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Found 8 papers, 3 papers with code
Vid2Coach: Transforming How-To Videos into Task Assistants
People use videos to learn new recipes, exercises, and crafts.
Lotus: Creating Short Videos From Long Videos With Abstractive and Extractive Summarization
Lotus first creates an abstractive short-form video by generating both a short-form script and its corresponding speech, then matching long-form video clips to the generated narration.
DreamStruct: Understanding Slides and User Interfaces via Synthetic Data Generation
Enabling machines to understand structured visuals like slides and user interfaces is essential for making them accessible to people with disabilities.
Long-Form Answers to Visual Questions from Blind and Low Vision People
Vision language models can now generate long-form answers to questions about images - long-form visual question answers (LFVQA).
Controlling Dialogue Generation with Semantic Exemplars
Dialogue systems pretrained with large language models generate locally coherent responses, but lack the fine-grained control over responses necessary to achieve specific goals.
Extracting Structured Data from Physician-Patient Conversations By Predicting Noteworthy Utterances
In this exploratory study, we describe a new dataset consisting of conversation transcripts, post-visit summaries, corresponding supporting evidence (in the transcript), and structured labels.
Investigating Evaluation of Open-Domain Dialogue Systems With Human Generated Multiple References
The aim of this paper is to mitigate the shortcomings of automatic evaluation of open-domain dialog systems through multi-reference evaluation.
How do people explore virtual environments?
Understanding how people explore immersive virtual environments is crucial for many applications, such as designing virtual reality (VR) content, developing new compression algorithms, or learning computational models of saliency or visual attention.
