Facebook, Inc.

Meta Platforms, Inc.

Shawn C P Mei

Vivek Natarajan

Zhengping Zuo

Rajen Subba

Wenhai Yang

Brian Nelson

Ashwini Challa

Alexander David Ramirez

Andrew Eugene Szeto

Anusha Balakrishnan

Necip Fazil Ayan

Scott Martin

Kartikeya Upasani

Donald Vincent Husa

In one embodiment, a method includes receiving at a head-mounted device a speech input from a user and a visual input captured by cameras of the head-mounted device, wherein the visual input comprises subjects and attributes associated with the subjects, and wherein the speech input comprises a co-reference to one or more of the subjects, resolving entities corresponding to the subjects associated with the co-reference based on the attributes and the co-reference, and presenting a communication content responsive to the speech input and the visual input at the head-mounted device, wherein the communication content comprises information associated with executing results of tasks corresponding to the resolved entities.

Processing multimodal user input for assistant systems

In one embodiment, a method includes, by one or more computing systems, receiving, by an assistant xbot associated with the one or more computing systems, a user request for a content digest, retrieving one or more content objects corresponding to the user request, generating one or more slides for the one or more retrieved content objects, respectively, and providing, by the assistant xbot, instructions for presenting the content digest responsive to the request from the first user, wherein the content digest comprises the one or more slides, and wherein one or more of the slides of the content digest are removed from the content digest after a predetermined time period.

Ephemeral content digests for assistant systems

In one embodiment, a method includes receiving a user input based on a plurality of modalities at the client system, wherein at least one of the modalities of the user input is a visual modality, determining one or more subjects and one or more attributes associated with the one or more subjects, respectively, based on the visual modality of the user input, resolving one or more entities corresponding to the one or more subjects based on the determined one or more attributes, and presenting a communication content at the client system responsive to the user input, wherein the communication content comprises information associated with executing results of one or more tasks corresponding to the one or more resolved entities.

Techniques for automated messaging are described. Some embodiments are particularly directed to techniques for automated business-to-consumer messaging leveraging social-networking information. In one embodiment, an apparatus may comprise a user profile component operative to retrieve a user profile associated with a user account for a messaging service and a messaging automation component operative to receive a messaging initiation from a messaging endpoint on a client device; and configure an automated response based on the user profile in response to the messaging initiation. Other embodiments are described and claimed.

Techniques for automated messaging

In one embodiment, a method includes receiving a user query from a client system associated with a first user, executing tasks via agents which return responses, each response comprising information items, analyzing the responses to determine slots, each slot corresponding to one of the information items, determining compositional sub-goals for each response, wherein each compositional sub-goal indicates a semantic-intent of the respective response, generating compositional fragments by a compositional natural-language generation (NLG) model, each compositional fragment comprising a partial natural-language response, determining a top-level compositional goal, generating a communication content by the compositional NLG model, wherein the communication content comprises a complete natural-language response to the user query, and wherein the complete natural-language response is based on the partial natural-language responses of the compositional fragments, and sending instructions for presenting the communication content to the client system.

Generating compositional natural language by assistant systems

In one embodiment, a method includes, by one or more computing systems, receiving, from a client system associated with a user, a request from the user for a content digest from an online social network, retrieving one or more content objects associated with the online social network that are accessible by the user, selecting one or more of the retrieved content objects to incorporate into the content digest based on their identified categories, generating one or more slides for the one or more selected content objects, respectively, wherein each slide comprises a summary and representative image of the respective selected content object, sending, to the client system of the user, instructions for presenting the content digest responsive to the request from the user, wherein the content digest comprises the one or more slides.

In one embodiment, a method includes receiving a user input from a client system associated with a user, generating a plurality of candidate responses by a natural-language generation module in response to the user input, determining a quality-indication by a filtering module for each candidate response of the plurality of candidate responses based on one or more classification models and one or more classification rules, wherein the classification models and classification rules are based on one or more acceptance-criteria, selecting one or more candidate responses from the plurality of candidate responses based on their respective quality-indications, ranking the selected candidate responses based on one or more ranking-criteria, and sending instructions for presenting a top-ranked candidate response to the user to the client system associated with the user responsive to receiving the user input.

Grammaticality classification for natural language generation in assistant systems

In one embodiment, a method includes receiving from a client system associated with a first user a user input based on one or more modalities, at least one of which is a visual modality, identifying one or more subjects associated with the user input based on the visual modality based on one or more machine-learning models, determining one or more attributes associated with the one or more subjects respectively based on the one or more machine-learning models, resolving one or more entities corresponding to the one or more subjects based on the determined one or more attributes, executing one or more tasks associated with the one or more resolved entities, and sending instructions for presenting a communication content including information associated with the executed one or more tasks responsive to user input to the client system associated with the first user.

This disclosure covers systems and methods that create references for locating a translation of a term expressed within a digital communication. In particular, in certain embodiments, the disclosed systems and methods create a hashkey to identify a translation (or multiple translations) of an initial term from a source language to a target language. By referring to this hashkey corresponding to the initial term, the disclosed systems and methods can identify a translation (or multiple translations) of the same or similar term within a digital communication to translate a digital communication from a source language to a target language.

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San Francisco, CA, United States of America

Shawn C P Mei