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AiSearch framework enables interactive multi-modal search with VLMs

By PulseAugur Editorial · [1 sources] ·

A new framework called AiSearch has been developed to enable interactive, multi-modal search capabilities using Vision Language Models (VLMs). This system allows users to refine search results in real-time through feedback and supports visual benchmarking across different VLMs to help users select the most appropriate model for their specific needs. AiSearch aims to bridge the gap between automated and interactive retrieval systems by leveraging the zero-shot abilities of VLMs for natural language searches over image and video content. AI

IMPACT Enhances search capabilities by enabling interactive, multi-modal queries over visual data using VLMs.

RANK_REASON The item describes a research paper detailing a new framework for multi-modal search. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AiSearch framework enables interactive multi-modal search with VLMs

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The item describes a research paper detailing a new framework for multi-modal search. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Ali Koksal, Mei Chee Leong, Vicky Sintunata, Ching Ling Chin, Wee Teck Fong ·

    AiSearch: Interactive Multi-Modal Search with VLMs

    arXiv:2610.01389v1 Announce Type: new Abstract: Modern retrieval systems must both be automated and interactive, allowing users to search and refine results in real time. We present AiSearch, a flexible multimodal retrieval framework that leverages the zero shot capabilities of V…

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