title: Pegasus-v1 Technical Report
summary: This technical report introduces Pegasus-1, a multimodal language model
  specialized in video content understanding and interaction through natural
  language. Pegasus-1 is designed to address the unique challenges posed by video
  data, such as interpreting spatiotemporal information, to offer nuanced video
  content comprehension across various lengths. This technical report overviews
  Pegasus-1's architecture, training strategies, and its performance in
  benchmarks on video conversation, zero-shot video question answering, and video
  summarization. We also explore qualitative characteristics of Pegasus-1 ,
  demonstrating its capabilities as well as its limitations, in order to provide
  readers a balanced view of its current state and its future direction.
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paper_authors.name: Jenny Ahn
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paper_authors.name: June Lee
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paper_authors.name: Maninder Saini
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paper_authors.name: Meredith Sanders
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paper_authors.name: Soyoung Lee
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paper_authors.name: Sue Kim
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paper_authors.name: Travis Couture
paper_title: Pegasus-v1 Technical Report
paper_summary: This technical report introduces Pegasus-1, a multimodal language model
  specialized in video content understanding and interaction through natural
  language. Pegasus-1 is designed to address the unique challenges posed by video
  data, such as interpreting spatiotemporal information, to offer nuanced video
  content comprehension across various lengths. This technical report overviews
  Pegasus-1's architecture, training strategies, and its performance in
  benchmarks on video conversation, zero-shot video question answering, and video
  summarization. We also explore qualitative characteristics of Pegasus-1 ,
  demonstrating its capabilities as well as its limitations, in order to provide
  readers a balanced view of its current state and its future direction.
paper_ai_summary: Pegasus-1 is a multimodal language model designed for video content comprehension, handling spatiotemporal information and demonstrated in benchmarks for video conversation, zero-shot video question answering, and video summarization.
paper_ai_keywords: multimodal language model video content understanding spatiotemporal information video conversation zero-shot video question answering video summarization