Adobe, Inc.

Ritiz Tambi

Ajinkya Gorakhnath Kale

Pranav Vineet Aggarwal

Sanyam Jain

Midhun Harikumar

Tracy Holloway King

Peter Evan O'Donovan

Venkata Naveen Kumar Yadav Marri

Rishabh Purwar

Sukriti Verma

Rishav Agarwal

Systems and methods for query processing are described. Embodiments of the present disclosure identify a target phrase in an original query, wherein the target phrase comprises a phrase to be replaced in the original query; replace the target phrase with a mask token to obtain a modified query; generate an alternative query based on the modified query using a masked language model (MLM), wherein the alternative query includes an alternative phrase in place of the target phrase that is consistent with a context of the target phrase; and retrieve a search result based on the alternative query.

Zero-shot entity-aware nearest neighbors retrieval

Embodiments are disclosed for machine learning-based generation of recommended layouts. The method includes receiving a set of design elements for performing generative layout recommendation. A number of each type of design element from the set of design elements is determined. A set of recommended layouts are generated using a trained generative layout model and the number and type of design elements. The set of recommended layouts are output.

Machine learning-based layout generation

Systems and methods for query processing are described. Embodiments of the present disclosure identify an original query; generate a plurality of expanded queries by generating a plurality of additional phrases based on the original query using a causal language model (CLM) and augmenting the original query with each of the plurality of additional phrases, respectively; and provide a plurality of images in response to the original query, wherein the plurality of images are associated with the plurality of expanded queries, respectively.

Generative prompt expansion for image generation

Systems and methods for natural language processing are described. Embodiments of the present disclosure receive plain text comprising a sequence of text entities; generate a sequence of entity embeddings based on the plain text, wherein each entity embedding in the sequence of entity embeddings is generated based on a text entity in the sequence of text entities; generate style information for the text entity based on the sequence of entity embeddings; and generate a document based on the style information.

Semantic structure identification for document autostyling

Systems and methods are disclosed for search query language identification. One method comprises generating a seed dictionary comprising a plurality of labeled dictionary terms and receiving a plurality of unlabeled sample query terms. The plurality of unlabeled sample query terms are compared to the plurality of labeled dictionary terms at a first time, and a first set of labeled sample query terms are generated by labeling at least a subset of the plurality of unlabeled sample query terms based on the first comparison. Remaining unlabeled sample query terms are then compared with the first set of labeled sample query terms at a second time, and a second set of labeled sample query terms are generated by labeling the remaining unlabeled sample query terms based on the second comparison. The first and second sets of labeled sample query terms are provided to a machine learning model configured for query language prediction.

Methods and systems for search query language identification

Introduced here is an approach to translating tags assigned to digital images. As an example, embeddings may be extracted from a tag to be translated and the digital image with which the tag is associated by a multimodal model. These embeddings can be compared to embeddings extracted from a set of target tags associated with a target language by the multimodal model. Such an approach allows similarity to be established along two dimensions, which ensures the obstacles associated with direct translation can be avoided.

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San Francisco, CA, United States of America

Ritiz Tambi