Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user at a virtual-reality (VR) headset, determining intents corresponding to the initial input by an intent-understanding module, generating candidate continuation-inputs in respective candidate modalities based on the intents, wherein the candidate modalities are different from the first modality, and presenting suggested inputs corresponding to one or more of the candidate continuation-inputs at the VR headset.

Abstract: A method includes detecting a user input comprising an incomplete three-dimensional (3D) gesture performed by one or more hands of a first user by a virtual-reality (VR) headset, selecting candidate 3D gestures from pre-defined 3D gestures based on a personalized gesture-recognition model, wherein each of the candidate 3D gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate 3D gesture, and presenting one or more suggested inputs corresponding to one or more of the candidate 3D gestures at the VR headset.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user from a client system associated with the first user, determining one or more intents corresponding to the initial input by an intent-understanding module, generating one or more candidate continuation-inputs based on the one or more intents, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, and wherein the candidate modalities are different from the first modality, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs to the client system.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user from a client system associated with the first user, determining one or more intents corresponding to the initial input by an intent-understanding module, generating one or more candidate continuation-inputs based on the one or more intents, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, and wherein the candidate modalities are different from the first modality, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs to the client system.

Abstract: In one embodiment, a method includes detecting a user input comprising an incomplete three-dimensional (3D) gesture performed by one or more hands of a first user by a virtual-reality (VR) headset, selecting candidate 3D gestures from pre-defined 3D gestures based on a personalized gesture-recognition model, wherein each of the candidate 3D gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate 3D gesture, and presenting one or more suggested inputs corresponding to one or more of the candidate 3D gestures at the VR headset.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user from a client system associated with the first user, determining one or more intents corresponding to the initial input by an intent-understanding module, generating one or more candidate continuation-inputs based on the one or more intents, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, and wherein the candidate modalities are different from the first modality, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs to the client system.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user from a client system associated with the first user, determining one or more intents corresponding to the initial input by an intent-understanding module, generating one or more candidate continuation-inputs based on the one or more intents, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, and wherein the candidate modalities are different from the first modality, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs to the client system.

Abstract: In one embodiment, a method includes detecting a user input comprising an incomplete gesture performed by one or more hands of a first user by a client system associated with the first user; selecting one or more candidate gestures from a plurality of pre-defined gestures by the client system based on a personalized gesture-recognition model, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and presenting one or more suggested inputs corresponding to one or more of the candidate gestures at the client system.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user at a client system, determining intents and slots corresponding to the initial input, wherein the slots are conditioned on the intents, generating one or more candidate continuation-inputs based on the intents and slots, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, wherein the candidate modalities are different from the first modality, and wherein each of the candidate continuation-inputs references entities represented by the slots, and presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs at the client system.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user from a client system associated with the first user, determining one or more intents corresponding to the initial input by an intent-understanding module, generating one or more candidate continuation-inputs based on the one or more intents, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, and wherein the candidate modalities are different from the first modality, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs to the client system.

Abstract: In one embodiment, a method includes receiving one or more inputs associated with proactive triggers associated with a first user, determining whether the first user is eligible to receive proactive suggestions based on one or more proactive policies, generating one or more proactive suggestions based on the one or more inputs and user context data associated with the first user, selecting one or more of the proactive suggestions based on task history data associated with the first user, and sending instructions for presenting proactive content to the first user to a client system associated the first user, wherein the proactive content comprises the selected proactive suggestions.

Abstract: In one embodiment, a method includes detecting a user input comprising an incomplete gesture performed by one or more hands of a first user by a client system associated with the first user; selecting one or more candidate gestures from a plurality of pre-defined gestures by the client system based on a personalized gesture-recognition model, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and presenting one or more suggested inputs corresponding to one or more of the candidate gestures at the client system.

Abstract: In one embodiment, a method includes receiving a user input from a client system associated with a first user, wherein the user input comprises an incomplete gesture performed by the first user, calculating one or more confidence scores by an intent-understanding module for one or more intents corresponding to the incomplete gesture, determining the calculated confidence scores associated with each of the intents are below a threshold score, selecting candidate gestures from a plurality of pre-defined gestures based on a personalized gesture-recognition model responsive to determining that the calculated confidence scores for each of the intents are below the threshold score, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate gestures to the client system.

Abstract: In one embodiment, a method includes receiving a user input from a client system associated with a first user, wherein the user input comprises an incomplete gesture performed by the first user, calculating one or more confidence scores by an intent-understanding module for one or more intents corresponding to the incomplete gesture, determining the calculated confidence scores associated with each of the intents are below a threshold score, selecting candidate gestures from a plurality of pre-defined gestures based on a personalized gesture-recognition model responsive to determining that the calculated confidence scores for each of the intents are below the threshold score, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate gestures to the client system.