MODEL TRAINING OF ACTOR MODEL AND CRITIC MODEL

    公开(公告)号:US20250061339A1

    公开(公告)日:2025-02-20

    申请号:US18936628

    申请日:2024-11-04

    Applicant: Lemon Inc.

    Abstract: Embodiments of the present disclosure provide a solution for model training. A method comprises: performing training of a critic model and training of an actor model according to an alternating scheme. The actor model is configured to generate a response for an input question based on a feedback generated by the critic model, and the critic model is configured to generate a feedback to a response generated by the actor mode.

    Secure computation and communication

    公开(公告)号:US12231563B2

    公开(公告)日:2025-02-18

    申请号:US18297339

    申请日:2023-04-07

    Applicant: Lemon Inc.

    Abstract: Methods and systems for secure computation and communication are provided. The method includes transforming identifications of a first dataset using a first transforming scheme, and transforming attributes of the first dataset using a second transforming scheme. The method also includes dispatching the transformed first dataset, receiving a second dataset, transforming identifications of the received second dataset, dispatching the identifications of the transformed received second dataset, and receiving a set of identifications. The method further includes generating a first intersection of the received set of identifications and the transformed received second dataset, generating a first share based on the first intersection, receiving a second share, and constructing a result based on the first share and the second share.

    VIDEO GENERATION METHOD AND DEVICE
    14.
    发明申请

    公开(公告)号:US20250054271A1

    公开(公告)日:2025-02-13

    申请号:US18723150

    申请日:2022-12-22

    Applicant: Lemon Inc.

    Abstract: The present disclosure provides a video generation method and device. The video generation method includes: extracting a first image feature from a first image; obtaining a plurality of intermediate image features by means of nonlinear interpolation according to the first image feature and a second image feature, wherein the second image feature is an image feature of a second image; and performing image reconstruction by means of an image generation model based on the first image feature, the second image feature, and the plurality of intermediate image features, so as to generate a target video, wherein the target video is used for presenting a process of a gradual change from the first image to the second image.

    TECHNIQUES FOR MODEL-BASED ELEMENT CREATION IN EFFECT CREATION TOOLS

    公开(公告)号:US20250053390A1

    公开(公告)日:2025-02-13

    申请号:US18447734

    申请日:2023-08-10

    Applicant: Lemon Inc.

    Abstract: Described are examples for creating elements in an effect creation tool, including receiving, via a user interface provided for the effect creation tool, a natural language string requesting creation of an element in the effect creation tool, providing, to a model, an input including at least a portion of the natural language string, receiving, from the model and based on the input, an output string, in an expected syntax, corresponding to creating the element, mapping the output string to one or more commands of a format for creating the element in the effect creation tool, and providing the one or more commands to the effect creation tool to cause creation of the element in the effect creation tool.

    METHOD, APPARATUS, STORAGE MEDIUM, AND ELECTRONIC DEVICE FOR FEATURE EXTRACTION

    公开(公告)号:US20250046054A1

    公开(公告)日:2025-02-06

    申请号:US18717239

    申请日:2023-03-17

    Abstract: The disclosure relates to a method, an apparatus, a storage medium, an electronic device, a computer program product, and a computer program for feature extraction, device. The method includes: determining target data for a feature to be extracted, and determining, based on the target data, a plurality of query vectors, a plurality of key vectors, and a plurality of value vectors; determining a plurality of key-value pair information corresponding to each of the query vectors; and performing, for each of the query vectors, a random mapping based on the query vector and the plurality of data samples, to obtain a plurality of random query vectors, and determining feature information corresponding to the query vector based on the plurality of random query vectors and the plurality of key-value pair information.

    SINGLE-STAGE OPEN-VOCABULARY PANOPTIC SEGMENTATION

    公开(公告)号:US20250045929A1

    公开(公告)日:2025-02-06

    申请号:US18365060

    申请日:2023-08-03

    Applicant: Lemon Inc.

    Abstract: Single-stage frameworks for open-vocabulary panoptic segmentation are provided. One aspect provides a computing system comprising a processor and memory storing instructions that, when executed by the processor, cause the processor to: receive an image; extract a plurality of feature maps from the image using a convolutional neural network-based vision-language model; generate a plurality of pixel features from the plurality of feature maps; generate a plurality of mask predictions from the plurality of pixel features; generate a plurality of in-vocabulary class predictions corresponding to the plurality of mask predictions using the plurality of pixel features; generate a plurality of out-of-vocabulary class predictions using the plurality of feature maps; perform geometric ensembling on the plurality of in-vocabulary class predictions and the plurality of out-of-vocabulary class predictions to generate a plurality of final class predictions; and output the plurality of mask predictions and the plurality of final class predictions.

    METHOD, APPARATUS, DEVICE AND MEDIUM FOR MANAGING MOLECULAR PREDICTION

    公开(公告)号:US20250037806A1

    公开(公告)日:2025-01-30

    申请号:US18717362

    申请日:2023-04-20

    Abstract: According to implementations of the present disclosure, a method, apparatus, device and medium for managing molecular prediction is provided. In the method, an upstream model is obtained from a portion of network layers in a pretrained model, the pretrained model describing an association between a molecular structure and molecular energy. A downstream model is determined based on a molecular prediction purpose, and an output layer of the downstream model is determined based on the molecular prediction purpose. A molecular prediction model is generated based on the upstream model and the downstream model, the molecular prediction model describing an association between a molecular structure and a molecular prediction purpose associated with the molecular structure. Since the upstream model may have extensive knowledge related to molecules, the amount of training data required to train the molecular prediction model that is generated based on the upstream model and the downstream model may be reduced.

    Neural Network-Based Post Filter For Video Coding

    公开(公告)号:US20250030881A1

    公开(公告)日:2025-01-23

    申请号:US18909092

    申请日:2024-10-08

    Applicant: Lemon Inc.

    Abstract: A method of processing video data. The method includes determining that a supplemental enhancement information (SEI) message of a bitstream includes indicators specifying one or more neural network (NN) filter model candidates or selections for a video unit or samples within the video unit, and converting between a video media file comprising the video unit and the bitstream based on the indicators. A corresponding video coding apparatus and non-transitory computer readable medium are also disclosed.

    Space manager for transparent block device compression

    公开(公告)号:US12204777B2

    公开(公告)日:2025-01-21

    申请号:US18187088

    申请日:2023-03-21

    Applicant: Lemon Inc.

    Abstract: Systems and methods for space allocation for block device compression are provided. In particular, a computing device may receive an allocation request to write the compressed data, select a range list adequate for serving the allocation request from a plurality of range list, dequeue a range entry from the selected range list to allocate free space for the compressed data, and allocate the free space corresponding to the range entry to the compressed data to serve the allocation request.

Patent Agency Ranking