# Text-to-Image Generative Modeling Without Language Pretraining

> **Publication**: aitalky (Independent AI Journalism)
> **Canonical Citation URL**: https://aitalky.vercel.app/news/text-to-image-generative-modeling-without-language-pretraining
> **Original Source**: [arXiv cs.AI](https://arxiv.org/abs/2610.26863v1)
> **Author**: Keshigeyan Chandrasegaran, Yue Zhao (undefined)
> **Published Date**: Monday, October 19, 2026
> **Category**: RESEARCH
> **Tags**: Research, arXiv, Machine Learning

## Executive Summary
Modern text-to-image (T2I) systems use internet-scale language pretraining for text-conditioned image generation. We ask whether language pretraining is necessary for strong T2I generation.



## Full Coverage
Focus to learn more arXiv-issued DOI via DataCite Submission history From: Keshigeyan Chandrasegaran [ view email ] [v1] Mon, 19 Oct 2026 17:59:59 UTC (7,942 KB) [v2] Tue, 20 Oct 2026 15:44:34 UTC (7,942 KB) Full-text links: Access Paper: View a PDF of the paper titled Text-to-Image Generative Modeling Without Language Pretraining, by Keshigeyan Chandrasegaran and 7 other authors View PDF HTML (experimental) TeX Source view license Additional Features Audio Summary Current browse context: cs.LG < prev | next > new | recent | 2026-10 Change to browse by: cs cs.CV References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) IArxiv recommender toggle IArxiv Recommender ( What is IArxiv? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website

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