Abstract: A method, apparatus, non-transitory computer readable medium, and system for generating a design document from a text prompt include obtaining a design prompt that describes a document type and selecting a design template for the document type based on the design prompt. An image generation model generates an image for the design template based on the design prompt and a design document is generated based on the design template. The design document has the document type and includes the image at a location indicated by the design template.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilizes embedding vectors to identify a subset of digital design templates to recommend to a client device based on individual user events. For instance, the disclosed systems extract metadata from digital design templates and generate, utilizing a transformer, a plurality of embedding vectors for the digital design templates from the extracted metadata. Further, the disclosed system generates, utilizing the transformer, a user embedding vector from one or more user events of a user. Moreover, the disclosed system utilizes identifies, utilizing a similarity search model, a subset of digital design templates from the digital design templates to recommend to the user by identifying one or more embedding vectors of the plurality of embedding vectors that satisfy a similarity threshold to the user embedding vector.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides to a user a subset of digital design templates as recommendations based on a creative segment classification and template classifications. For instance, in one or more embodiments, the disclosed systems generate the creative segment classification for the user and determines geo-seasonal intent data. Furthermore, the disclosed system generates template classifications using a machine learning model based on geo-seasonality and creative intent. In doing so, the disclosed system identifies a subset of digital design templates based on the template classifications, geo-seasonal intent data, and the creative segment classification of the user.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides to a user a subset of digital design templates as recommendations based on a creative segment classification and template classifications. For instance, in one or more embodiments, the disclosed systems generate the creative segment classification for the user and determines geo-seasonal intent data. Furthermore, the disclosed system generates template classifications using a machine learning model based on geo-seasonality and creative intent. In doing so, the disclosed system identifies a subset of digital design templates based on the template classifications, geo-seasonal intent data, and the creative segment classification of the user.

Abstract: An electrically conductive and corrosion resistant graphene-based coating composition, including a binder, high-pressure airless-sprayed expanded graphene stacks, carbon fibers, and a dispersing agent, wherein the graphene-based coating composition has an electrical conductivity of at least 2 S/cm and a pull-off adhesion of at least 2 MPa.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides to a user a subset of digital design templates as recommendations based on a creative segment classification and template classifications. For instance, in one or more embodiments, the disclosed systems generate the creative segment classification for the user and determines geo-seasonal intent data. Furthermore, the disclosed system generates template classifications using a machine learning model based on geo-seasonality and creative intent. In doing so, the disclosed system identifies a subset of digital design templates based on the template classifications, geo-seasonal intent data, and the creative segment classification of the user.

Abstract: In implementations of systems for identifying templates based on fonts, a computing device implements an identification system to receive input data describing a selection of a font included in a collection of fonts. The identification system generates an embedding that represents the font in a latent space using a machine learning model trained on training data to generate embeddings for digital templates in the latent space based on intent phrases associated with the digital templates and embeddings for fonts in the latent space based on intent phrases associated with the fonts. A digital template included in a collection of digital templates is identified based on the embedding that represents the font and an embedding that represents the digital template in the latent space. The identification system generates an indication of the digital template for display in a user interface.

Abstract: An electrically conductive and corrosion resistant graphene-based coating composition, including a binder, high-pressure airless-sprayed expanded graphene stacks, carbon fibers, and a dispersing agent, wherein the graphene-based coating composition has an electrical conductivity of at least 2 S/cm and a pull-off adhesion of at least 2 MPa.

Abstract: An electrically conductive and corrosion resistant graphene-based coating composition, including a binder, a graphene-filler; and a dispersing agent, wherein the graphene filler comprises a plurality of graphene stacks.

Abstract: An electrically conductive and corrosion resistant graphene-based coating composition, including a binder, a graphene-filler; and a dispersing agent, wherein the graphene filler comprises a plurality of graphene stacks.