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LLM-powered ToolMerge improves video keyframe retrieval

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new method called ToolMerge for retrieving keyframes from long videos, which is particularly useful for question-answering tasks. This approach utilizes a Large Language Model (LLM) to break down complex queries into smaller tool calls and then merges the results. The method was evaluated on a new benchmark called Molmo-2 Moments (M2M) and showed a 5% improvement in caption retrieval compared to existing techniques. AI

IMPACT Introduces a novel LLM-based approach for video keyframe retrieval, potentially improving AI's ability to understand and query long video content.

RANK_REASON The cluster contains an academic paper detailing a new method and benchmark.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLM-powered ToolMerge improves video keyframe retrieval

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The cluster contains an academic paper detailing a new method and benchmark.
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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Michal Shlapentokh-Rothman, Prachi Garg, Yu-Xiong Wang, Derek Hoiem ·

    Decomposing Queries into Tool Calls for Long-Video Keyframe Retrieval

    arXiv:2605.23826v1 Announce Type: cross Abstract: Keyframe selection is a direct way to provide verifiable visual evidence for long-video question answering (QA). Queries differ in what they require, and finding the right frames depends on knowing what to look for. Existing keyfr…

  2. arXiv cs.CV TIER_1 English(EN) · Derek Hoiem ·

    Decomposing Queries into Tool Calls for Long-Video Keyframe Retrieval

    Keyframe selection is a direct way to provide verifiable visual evidence for long-video question answering (QA). Queries differ in what they require, and finding the right frames depends on knowing what to look for. Existing keyframe selectors either score every frame against a s…

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