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TimeSearch: Hierarchical Video Search with Spotlight and Reflection for Human-like Long Video Understanding

arXiv — cs.CV•Wednesday, December 3, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
  • TimeSearch has been introduced as a novel framework designed to enhance the understanding of long videos by Large Video-Language Models (LVLMs). This framework incorporates two human-like strategies: Spotlight, which identifies relevant temporal events, and Reflection, which evaluates the correctness of these events, addressing the challenges posed by visual hallucinations in long video processing.
  • The development of TimeSearch is significant as it aims to improve the accuracy and efficiency of LVLMs in interpreting lengthy video content, which has been a persistent challenge in the field of artificial intelligence and video analysis. By mimicking human hierarchical search strategies, this framework could lead to more reliable video understanding applications.
  • This advancement reflects a broader trend in AI research focusing on enhancing video comprehension through innovative frameworks. Similar initiatives, such as Agentic Video Intelligence and SMART, emphasize the integration of complex reasoning and multimodal capabilities, indicating a growing recognition of the need for sophisticated tools that can handle the intricacies of video data in a human-like manner.
— via World Pulse Now AI Editorial System
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