Sequence-to-sequence prediction using a neural network model

    公开(公告)号:US11604956B2

    公开(公告)日:2023-03-14

    申请号:US15885576

    申请日:2018-01-31

    Abstract: A method for sequence-to-sequence prediction using a neural network model includes A method for sequence-to-sequence prediction using a neural network model, generating an encoded representation based on an input sequence using an encoder of the neural network model, predicting a fertility sequence based on the input sequence, generating an output template based on the input sequence and the fertility sequence, and predicting an output sequence based on the encoded representation and the output template using a decoder of the neural network model. The neural network model includes a plurality of model parameters learned according to a machine learning process. Each item of the fertility sequence includes a fertility count associated with a corresponding item of the input sequence.

    Interest groups based on network feed items

    公开(公告)号:US11604814B2

    公开(公告)日:2023-03-14

    申请号:US17249162

    申请日:2021-02-22

    Inventor: Ashok Gadamsetty

    Abstract: Disclosed are some examples of systems, apparatus, methods and storage media for creating groups in a social networking database system, and more specifically, to creating groups based on network feed items. In some implementations, a database system is capable of maintaining a database including data associated with a plurality of users and groups to which the users can be subscribed. The system is configurable to provide a feed for display to a first user, and to receive input entered in a publication field by the first user. The system is configurable to create a feed item for display to the first user and to at least one second user based on the received input. The system is configurable to receive second input associated with the feed item from the second user. The system is additionally configurable to provide a selectable user interface (UI) element for display to the first user. Responsive to the selection of the UI element, the system is further configurable to create a new group based on the feed item, and to subscribe the first and the second user to the new group without additional input.

    WORKFLOWS FOR AUTOMATED OPERATIONS MANAGEMENT

    公开(公告)号:US20230073909A1

    公开(公告)日:2023-03-09

    申请号:US18055489

    申请日:2022-11-15

    Inventor: Mark F. Wilding

    Abstract: Techniques are disclosed relating to automated operations management. In various embodiments, a computer system accesses operational information that defines commands for an operational scenario and accesses blueprints that describe operational entities in a target computer environment related to the operational scenario. The computer system implements the operational scenario for the target computer environment. The implementing may include executing a hierarchy of controller modules that include an orchestrator controller module at top level of the hierarchy that is executable to carry out the commands by issuing instructions to controller modules at a next level. The controller modules may be executable to manage the operational entities according to the blueprints to complete the operational scenario. In various embodiments, the computer system includes additional features such as an application programming interface (API), a remote routing engine, a workflow engine, a reasoning engine, a security engine, and a testing engine.

    SYSTEMS AND METHODS FOR SEQUENTIAL RECOMMENDATION

    公开(公告)号:US20230073754A1

    公开(公告)日:2023-03-09

    申请号:US17586451

    申请日:2022-01-27

    Abstract: Embodiments described herein provides an intent prototypical contrastive learning framework that leverages intent similarities between users with different behavior sequences. Specifically, user behavior sequences are encoded into a plurality of user interest representations. The user interest representations are clustered into a plurality of clusters based on mutual distances among the user interest representations in a representation space. Intention prototypes are determined based on centroids of the clusters. A set of augmented views for user behavior sequences are created and encoded into a set of view representations. A contrastive loss is determined based on the set of augmented views and the plurality of intention prototypes. Model parameters are updated based at least in part on the contrastive loss.

    SYSTEMS AND METHODS FOR EXPLAINABLE AND FACTUAL MULTI-DOCUMENT SUMMARIZATION

    公开(公告)号:US20230070497A1

    公开(公告)日:2023-03-09

    申请号:US17589675

    申请日:2022-01-31

    Abstract: Embodiments described herein provide methods and systems for summarizing multiple documents. A system receives a plurality of documents and generates embeddings of the sentences from the plurality of documents. The embedded sentences are clustered in a representation space. Sentences from a reference summary are embedded and aligned with the closest cluster. Sentences from each cluster are summarized with the aligned reference sentences as a target. A loss is computed based on the summarized sentences and the aligned references, and the natural language processing model is updated based on the loss. Sentences may be masked from being used in the summarization by identifying sentences that are contradicted by other sentences within the plurality of documents.

    System and method for learning with noisy labels as semi-supervised learning

    公开(公告)号:US11599792B2

    公开(公告)日:2023-03-07

    申请号:US16688104

    申请日:2019-11-19

    Abstract: A method provides learning with noisy labels. The method includes generating a first network of a machine learning model with a first set of parameter initial values, and generating a second network of the machine learning model with a second set of parameter initial values. First clean probabilities for samples in a training dataset are generated using the second network. A first labeled dataset and a first unlabeled dataset are generated from the training dataset based on the first clean probabilities. The first network is trained based on the first labeled dataset and first unlabeled dataset to update parameters of the first network.

    Intelligent training set augmentation for natural language processing tasks

    公开(公告)号:US11599721B2

    公开(公告)日:2023-03-07

    申请号:US17002562

    申请日:2020-08-25

    Abstract: A natural language processing system that trains task models for particular natural language tasks programmatically generates additional utterances for inclusion in the training set, based on the existing utterances in the training set and the existing state of a task model as generated from the original (non-augmented) training set. More specifically, the training augmentation module 220 identifies specific textual units of utterances and generates variants of the utterances based on those identified units. The identification is based on determined importances of the textual units to the output of the task model, as well as on task rules that correspond to the natural language task for which the task model is being generated. The generation of the additional utterances improves the quality of the task model without the expense of manual labeling of utterances for training set inclusion.

    METRIC PRESENTATION WITHIN A FLOW BUILDER

    公开(公告)号:US20230067380A1

    公开(公告)日:2023-03-02

    申请号:US17823697

    申请日:2022-08-31

    Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for executing process flows. A graphical representation of a flow is provided for presentation via a display device, where the flow includes a plurality of elements, each of the elements corresponding to a set of computer-readable instructions. A set of metrics associated with the flow is generated or updated, where the set of metrics indicates, for each of a plurality of paths of the flow, one or more metrics collected across a plurality of users of the database system that accessed the flow, each of the paths of the flow corresponding to a subset of the plurality of elements of the flow. An indication of the set of metrics associated with the flow is provided, for presentation via the display device, in relation to one or more elements of the flow such that at least a first portion of the set of metrics is provided for presentation in close proximity to a visual representation of a first one of the elements of the flow and a second portion of the set of metrics is provided for presentation in close proximity to a visual representation of a second one of the elements of the flow. A request to modify the flow is processed and the graphical representation of the flow is modified responsive to processing the request to modify the flow. In addition, a modified flow corresponding to the modified graphical representation can be stored.

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