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A Tutorial on World Models and Physical AI

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arXiv:2606. 12783v1 Announce Type: new Abstract: World modeling is emerging as a central principle for building intelligent systems capable of prediction, reasoning, and decision making.

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Authors: Il-Seok Oh
Released: 2026-06-12 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because A Tutorial on World Models and Physical AI overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: code, under, control, model. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2606.12783

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