Generating Illustrated Instructions
We introduce the new task of generating Illustrated Instructions, i.e.,
visual instructions customized to a user's needs. We identify desiderata unique
to this task, and formalize it through a suite of automatic and human
evaluation metrics, designed to measure the validity, consistency, and efficacy
of the generations. We combine the power of large language models (LLMs)
together with strong text-to-image generation diffusion models to propose a
simple approach called StackedDiffusion, which generates such illustrated
instructions given text as input. The resulting model strongly outperforms
baseline approaches and state-of-the-art multimodal LLMs; and in 30% of cases,
users even prefer it to human-generated articles. Most notably, it enables
various new and exciting applications far beyond what static articles on the
web can provide, such as personalized instructions complete with intermediate
steps and pictures in response to a user's individual situation.
65727e599a5c2d6df9f257cd
Sachit Menon
admin_assigned
2023-12-08T10:58:13.690Z
62fbbfaa7a577e83ccccbffb
/avatars/f4e8cf1e9145a1df39082544eb709264.svg
Sachit Menon
user
sachit-menon
65727e599a5c2d6df9f257ce
Ishan Misra
admin_assigned
2023-12-08T10:58:20.906Z
63faa5b04380ab0cb9577a57
/avatars/c71be0acb0553671c9703654e998cbd5.svg
Ishan Misra
user
hayhay404
65727e599a5c2d6df9f257cf
Rohit Girdhar
admin_assigned
2023-12-08T10:58:27.544Z
63c6c737656e7822e23732d8
/avatars/3cf062864dbf2b5423eb1f4beaeec1ea.svg
Rohit Girdhar
user
rgirdhar
Generating Illustrated Instructions
We introduce the new task of generating Illustrated Instructions, i.e.,
visual instructions customized to a user's needs. We identify desiderata unique
to this task, and formalize it through a suite of automatic and human
evaluation metrics, designed to measure the validity, consistency, and efficacy
of the generations. We combine the power of large language models (LLMs)
together with strong text-to-image generation diffusion models to propose a
simple approach called StackedDiffusion, which generates such illustrated
instructions given text as input. The resulting model strongly outperforms
baseline approaches and state-of-the-art multimodal LLMs; and in 30% of cases,
users even prefer it to human-generated articles. Most notably, it enables
various new and exciting applications far beyond what static articles on the
web can provide, such as personalized instructions complete with intermediate
steps and pictures in response to a user's individual situation.
StackedDiffusion, combining LLMs and text-to-image diffusion models, generates personalized illustrated instructions that outperform existing methods and user preferences.
large language models LLMs diffusion models text-to-image generation StackedDiffusion