LLaVA-OneVision: Single-Image, Multi-Image, Video in One Model
Before LLaVA-OneVision (Li et al., August 2024) the open-VLM world had separate lineages: LLaVA-1.5 for single images, multi-image models like Mantis and VILA, video models like Video-LLaVA and Video-LLaMA. Each won its benchmark and failed at the others. LLaVA-OneVision argued a single curriculum could train one model to dominate all three scenarios, and that the emergent task-transfer effects (single-image skills exported to video, multi-image reasoning exported to single-image) beat the sum of specialists. The recipe is deceptively simple: a visual-token budget that stays constant across scenarios, plus an explicit curriculum that moves from single-image to OneVision (multi-image) to video. This lesson reads the budget, the curriculum, and the emergent behaviors.
This lesson isn’t interactive yet.
It is part of the curriculum and will get the same treatment as Phase 1 — a visual cover, hands-on labs, derivations with numeric checks and a quiz. Until then, the original lesson is the best place to read it:
Part of Phase 12 — Multimodal AI. Use the previous / next cards below to keep browsing the phase.