AI & ML
Substantial, Decomposable, and Invisible: Visual Context Misalignment in Instructional Videos for Physical Tasks
arXiv cs.HC0 views
arXiv:2605.17184v2 Announce Type: replace Abstract: Instructional videos are the dominant medium for completing physical tasks, yet rarely match the user's visual context. Motor simulation and cognitive load theories predict this mismatch matters, but how much, which attributes are responsible, and how users experience it remain unknown. We conduct two studies (56 participants, two first-aid and two cooking tasks) using researcher-prepared recordings to control visual alignment. Study 1 (N=16) compares fully aligned In-Context instructional videos (ICON) against business-as-usual Internet videos. ICON yields statistically significant gains: 11.1% higher completion quality and 15.5% faster completion. Qualitative analysis decomposes the effect into four visual context attributes: Task Object Intrinsic, Task Object State, Environmental Context, and Observational Context. Study 2 (N=40) ablates attributes one at a time. All four degrade objective performance yet users perceive no performance loss for any of them. Visual context misalignment is substantial, decomposable, and invisible to the user for any single attribute.
Source:https://arxiv.org/abs/2605.17184PreviousEvoDesign: Agentic Editable Diagram Creation via Design Expertise EvolutionNextTowards fNIRS foundation models: A curated corpus of 67 public datasets with channel positions in MNI space
Related posts

How I Switched: a human-approved change desk for AI agents
0dev.to
Your favourite name is taken. Do not ruin it trying to save it
0dev.to
Writing HTCondor DAG Files: Job Dependencies, Variables, and Concurrency Limits
0dev.to
YuGPT backs up ChatGPT and Codex chats locally and offers flexible search across them. It's quietly finding buyers. Thank you to everyone who bought it. I'm working on improvements and plan to release
0dev.to
GEO 的第一步,不是多發幾篇文章
0dev.to AI
Sol's Take: Saturday — November 07, 2026
0dev.to AI