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AI researchers debate multimodal embedding strategies for text-only search

By PulseAugur Editorial · [1 sources] ·

A user on Reddit's r/MachineLearning subreddit is seeking advice on how to implement text-only vector search within a multimodal embedding space. The user's dataset consists of images paired with descriptive text. They are weighing whether to embed text and image components as separate vectors or combine them into a single vector, considering how text-only queries might affect search results. AI

IMPACT Discusses technical challenges in multimodal AI search implementation.

RANK_REASON User query seeking technical advice on AI implementation.

Read on r/MachineLearning →

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

AI researchers debate multimodal embedding strategies for text-only search

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User query seeking technical advice on AI implementation.
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COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/AdaObvlada ·

    How to deal with text only vector search across multimodal embedding space? [D]

    <!-- SC_OFF --><div class="md"><p>My data set is a list of images, each equipped with a a couple sentences of text.</p> <p>A user would search primarily with text only. My default approach is using BM25, but how would I facilitate searching with a vector DB and a model that embed…

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