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20182025
most citedDetecting Hate Speech and Offensive Language on Twitter using Machine Learning: An N-gram and TFIDF based Approach

96 citations · 98 across the 5 of their papers we have counts for

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Showing 2024Show all

2 papers · 1 filter

cs.CV2024★ 1 cited

xGen-MM-Vid (BLIP-3-Video): You Only Need 32 Tokens to Represent a Video Even in VLMs

Michael S. Ryoo, Honglu Zhou, Shrikant Kendre +9

We present xGen-MM-Vid (BLIP-3-Video): a multimodal language model for videos, particularly designed to efficiently capture temporal information over multiple frames. BLIP-3-Video…

cs.CV2024★ 1 cited

xGen-MM (BLIP-3): A Family of Open Large Multimodal Models

Le Xue, Manli Shu, Anas Awadalla +30

This paper introduces BLIP-3, an open framework for developing Large Multimodal Models (LMMs). The framework comprises meticulously curated datasets, a training recipe, model archi…