In one embodiment, a method includes, by a client system, receiving a user input from the first user of an online social network, where the user input is associated with a subject and an intent, determining whether one or more agents associated with the intent are able to resolve the user input, identifying, responsive to determining that the one or more agents are not able to resolve the user input, one or more entities related to the subject, where each identified entity is connected to the first user via the online social network, and presenting, at the client system, one or more recommendations to the first user corresponding to the one or more entities.

In one embodiment, a method includes, by one or more computing systems, receiving, at the client system, a first user input, processing, by the client system, the first user input to provide an initial response by identifying one or more entities referenced by the first user input and providing, by the client system, the initial response, where the initial response comprises a conversational filler referencing at least one of the one or more identified entities, processing the first user input to provide a complete response by identifying, by the client system, one or more intents and one or more slots associated with the first user input based on a semantic analysis by a natural-language understanding module and providing, by the client system, the complete response subsequent to the initial response, where the complete response is based on the one or more intents and the one or more slots.

In one embodiment, a method includes receiving a user request from a first user from a client system associated with a first user, wherein the user request comprise a gesture-input from the first user and a speech-input from the first user, determining an intent corresponding to the user request based on the gesture-input by a personalized gesture-classification model associated with the first user, executing one or more tasks based on the determined intent and the speech-input, and sending instructions for presenting execution results of the one or more tasks to the client system responsive the user request.

In one embodiment, a method includes, by one or more computing systems, receiving, from a client system, an input in a multi-turn message thread, parsing the input to identify a plurality of hypothesis dialog states associated with the input, generating a plurality of functions corresponding to the plurality of hypothesis dialog states, calculating a plurality of probability scores for the plurality of functions, respectively, based on a prior dialog state associated with the message thread and a current user context, wherein each probability score represents a likelihood that the respective function is associated with an intended dialog state, and storing the plurality of functions if each of the probability scores is below a threshold probability score, wherein the plurality of functions is stored as a hierarchical set of functions that is used as the prior dialog state in response to a next input in the message thread.

Systems and methods for improving database system performance are described. In one embodiment, a database system includes a database application cluster including at least one read-write node and a plurality of read nodes, a shared memory, and a multiplexer coupled to the database application cluster and shared memory. The multiplexer is configured to receive a request from a client computing system which includes a database query. Based on a lookup in the shared memory, the multiplexer determines that the database query can be routed to one of the plurality of read nodes. In response, the database query is routed to one of the read nodes for execution.

In one embodiment, a method includes receiving a user query associated with dialog-intents at a client system, executing tasks corresponding to the dialog-intents, generating a multi-perspective response by a stitching model based on two or more of execution results of the tasks, wherein the multi-perspective response comprises a natural-language response combining the two or more execution results, and presenting the multi-perspective response at the client system.

In one embodiment, a method includes receiving a user input by a user from a client system associated with the user, parsing the user input to identify a subject and intent of the user input, determining whether one or more agents associated with the identified intent are able to resolve the user input, identifying one or more entities related to the identified subject of the user input responsive to determining that the one or more agents are not able to resolve the user input, calculating a subject-association score for each of the one or more entities, ranking the one or more entities based on their respective subject-association scores, and sending, to the client system, instructions for presenting one or more recommendations to the user corresponding to one or more of the entities having a ranking greater than a threshold ranking.

In one embodiment, a method includes receiving a user query from a client system associated with a first user, determining a plurality of dialog-intents, each being associated with a particular agent of a plurality of agents, executing a plurality of tasks corresponding to the user query via the plurality of agents corresponding to the plurality of dialog-intents, receiving a plurality of execution results corresponding to the plurality of tasks from the plurality of agents, respectively, selecting two or more of the plurality of execution results for combination, generating a multi-perspective response based on the selected execution results by a stitching model, wherein the multi-perspective response comprises a natural-language response combining the selected execution results, and sending instructions for presenting the multi-perspective response to the first user to the client system in response to the user query.

In one embodiment, a method includes receiving one or more voice inputs from a first user, determining a first language register associated with the first user based on the one or more voice inputs, selecting a second language register for a voice response based on the one or more voice inputs, generating the voice response based on the second language register, and providing the voice response in response to the one or more voice inputs.

In one embodiment, a method includes receiving a first user input by a first user at a client system associated with the first user, wherein the first user input is associated with a first language register, selecting a first language-register model from a plurality of language-register models based on the first language register by the client system, wherein the plurality of language-register models are each personalized with respect to the first user, and presenting a personalized first communication content generated based on the selected first language-register model at the client system.