Visual Document Pretraining Beats Text-Only
KyeGomezB · x · 2026-07-13
The paper "Scalable Visual Pretraining for Language Intelligence" explores a counterintuitive approach:
- Instead of relying solely on plain text as pretraining data, they train language models directly on visual documents.
- Training materials include visual information like charts, formulas, and layouts.
- Results show this method outperforms text-only pretraining, challenging the default assumption that LMs must start by learning from plain text.
The core conclusion emphasized is that visual documents contain an abundance of structured signals useful for developing language intelligence.
Related event: Scalable Visual Pretraining Boosts Language Intelligence(4 posts)→
More from Research
- Structural ensembles beat single predictions in TCR:pMHC generalization study — quaidmorris · 2026-07-22
- Structural ensembles, not single predictions, drive robust TCR:pMHC generalization — quaidmorris · 2026-07-22
- A 3D ray plot shows how hard this Jacobian counterexample is to read — moultano · 2026-07-22
- LLM leaderboards are now often measuring the harness too, Gary Marcus warns — GaryMarcus · 2026-07-22
- New paper defines self-state attacks, showing OS defenses leave four agent-memory cases indistinguishable — Justgototheeffinmoon · 2026-07-22
- Krea 2 users recommend a two-pass Clownshark sampler setup for sharper image details — listopalafoto · 2026-07-22