Patents by Inventor Tong Sun
Tong Sun has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11914635Abstract: Systems and methods for image searching are described. The systems and methods include receiving a search query comprising user input for a reference image; converting the user input for the reference image to a preference statement using a machine learning model; encoding the preference statement in an embedding space to obtain an encoded preference statement; combining the encoded preference statement with an encoded reference image representing the reference image in the embedding space to obtain a multi-modal search encoding; and performing a search operation using the multi-modal search encoding to retrieve a second image, wherein the second image differs from the reference image based on the user input for the reference image.Type: GrantFiled: November 19, 2021Date of Patent: February 27, 2024Assignee: ADOBE INC.Inventors: Victor Soares Bursztyn, Jennifer Anne Healey, Vishwa Vinay, Tong Sun
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Publication number: 20240056309Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media that fill in digital documents using user identity models of client devices. For instance, in one or more embodiments, the disclosed systems receive a digital document comprising a digital fillable field. The disclosed systems further retrieve, for a client device associated with the digital document, a decentralized identity credential comprising a user attribute established under a decentralized identity framework. Using the user attribute of the decentralized identity credential, the disclosed systems modify the digital document by filling in the digital fillable field.Type: ApplicationFiled: August 12, 2022Publication date: February 15, 2024Inventors: Songlin He, Tong Sun, Nedim Lipka, Curtis Wigington, Rajiv Jain, Anindo Roy
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Publication number: 20240048475Abstract: An information processing method, an interconnection device, and a computer-readable storage medium are provided. The interconnection device includes a request processing module configured for: receiving a data access request from at least one processor, wherein the data access request comprises a merge bit, a multicast group identifier (MGID), and a multicast transaction identifier (MTID); determining whether the data access request is a multicast request; determining whether the interconnection device receives other multicast requests if it is determined that the data access request is a multicast request based on the MGID, the MTID, and a static routing policy of a multicast group; and obtaining the other multicast requests if it is determined that the interconnection device receives the other multicast requests, merging the multicast request with the other multicast requests into a merged request, and forwarding the merged request to a next-hop device of the interconnection device.Type: ApplicationFiled: October 15, 2023Publication date: February 8, 2024Applicant: Shanghai Biren Technology Co.,LtdInventors: Qin ZHENG, Zhou HONG, YuFei ZHANG, Lin CHEN, ChengKun SUN, Tong SUN, ChengPing LUO, HaiChuan WANG
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Patent number: 11886815Abstract: One example method involves operations for a processing device that include receiving, by a machine learning model trained to generate a search result, a search query for a text input. The machine learning model is trained by receiving pre-training data that includes multiple documents. Pre-training the machine learning model by generating, using an encoder, feature embeddings for each of the documents included in the pre-training data. The feature embeddings are generated by applying a masking function to visual and textual features in the documents. Training the machine learning model also includes generating, using the feature embeddings, output features for the documents by concatenating the feature embeddings and applying a non-linear mapping to the feature embeddings. Training the machine learning model further includes applying a linear classifier to the output features. Additionally, operations include generating, for display, a search result using the machine learning model based on the input.Type: GrantFiled: May 28, 2021Date of Patent: January 30, 2024Assignee: ADOBE INC.Inventors: Jiuxiang Gu, Vlad Morariu, Varun Manjunatha, Tong Sun, Rajiv Jain, Peizhao Li, Jason Kuen, Handong Zhao
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Patent number: 11855878Abstract: An information processing method, an interconnection device, and a computer-readable storage medium are provided. The interconnection device includes a request processing module configured for: receiving a data access request from at least one processor, wherein the data access request comprises a merge bit, a multicast group identifier (MGID), and a multicast transaction identifier (MTID); determining whether the data access request is a multicast request; determining whether the interconnection device receives other multicast requests if it is determined that the data access request is a multicast request based on the MGID, the MTID, and a static routing policy of a multicast group; and obtaining the other multicast requests if it is determined that the interconnection device receives the other multicast requests, merging the multicast request with the other multicast requests into a merged request, and forwarding the merged request to a next-hop device of the interconnection device.Type: GrantFiled: November 11, 2021Date of Patent: December 26, 2023Assignee: Shanghai Biren Technology Co., LtdInventors: Qin Zheng, Zhou Hong, YuFei Zhang, Lin Chen, ChengKun Sun, Tong Sun, ChengPing Luo, HaiChuan Wang
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Publication number: 20230376687Abstract: Embodiments are provided for facilitating multimodal extraction across multiple granularities. In one implementation, a set of features of a document for a plurality of granularities of the document is obtained. Via a machine learning model, the set of features of the document are modified to generate a set of modified features using a set of self-attention values to determine relationships within a first type of feature and a set of cross-attention values to determine relationships between the first type of feature and a second type of feature. Thereafter, the set of modified features are provided to a second machine learning model to perform a classification task.Type: ApplicationFiled: May 17, 2022Publication date: November 23, 2023Inventors: Vlad Ion Morariu, Tong Sun, Nikolaos Barmpalios, Zilong Wang, Jiuxiang Gu, Ani Nenkova Nenkova, Christopher Tensmeyer
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Publication number: 20230377363Abstract: Systems and methods for machine learning based multipage scanning are provided. In one embodiment, one or more processing devices perform operations that include receiving a video stream that includes image frames that capture a plurality of pages of a document. The operations further include detection, via a machine learning model that is trained to infer events from the video stream detects, a new page event. Detection of the new page event indicates that a page of the plurality of pages available for scanning has changed from a first page to a second page. Based on the detection of the new page event, the one or more processing devices capture an image frame of the page from the video stream. In some embodiments, the machine learning model detects events based on a weighted use of video data, inertial data, audio samples, image depth information, image statistics and/or other information.Type: ApplicationFiled: May 17, 2022Publication date: November 23, 2023Inventors: Tong SUN, Nicholas Sergei REWKOWSKI, Nedim LIPKA, Jennifer Anne HEALEY, Curtis Michael WIGINGTON, Anshul MALIK
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Publication number: 20230368003Abstract: The technology described herein is directed to an adaptive sparse attention pattern that is learned during fine-tuning and deployed in a machine-learning model. In aspects, a row or a column in an attention matrix with an importance score for a task that is above a threshold importance score is identified. The important row or the column is included in an adaptive attention pattern used with a machine-learning model having a self-attention operation. In response to an input, a task-specific inference is generated for the input using the machine-learning model with the adaptive attention pattern.Type: ApplicationFiled: May 10, 2022Publication date: November 16, 2023Inventors: Jiuxiang Gu, Zihan Wang, Jason Wen Yong Kuen, Handong Zhao, Vlad Ion Morariu, Ruiyi Zhang, Ani Nenkova Nenkova, Tong Sun
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Patent number: 11816243Abstract: Systems, methods, and non-transitory computer-readable media can generate a natural language model that provides user-entity differential privacy. For example, in one or more embodiments, a system samples sensitive data points from a natural language dataset. Using the sampled sensitive data points, the system determines gradient values corresponding to the natural language model. Further, the system generates noise for the natural language model. The system generates parameters for the natural language model using the gradient values and the noise, facilitating simultaneous protection of the users and sensitive entities associated with the natural language dataset. In some implementations, the system generates the natural language model through an iterative process (e.g., by iteratively modifying the parameters).Type: GrantFiled: August 9, 2021Date of Patent: November 14, 2023Assignee: Adobe Inc.Inventors: Thi Kim Phung Lai, Tong Sun, Rajiv Jain, Nikolaos Barmpalios, Jiuxiang Gu, Franck Dernoncourt
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Patent number: 11732374Abstract: Reaction products of amines and polymers containing saturated heterocyclic moieties may be used as levelers in metal electroplating baths. The reaction products may plate metal with good surface properties and good physical reliability.Type: GrantFiled: January 17, 2020Date of Patent: August 22, 2023Assignees: Rohm and Haas Electronic Materials LLC, Dow Global Technologies LLCInventors: Lingli Duan, Chen Chen, Tong Sun, Zukhra I. Niazimbetova, Maria Anna Rzeznik
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Publication number: 20230236072Abstract: There is provided a semiconductor device 100, comprising: at least one semiconductor chip 5, and a structure 2 thermally coupled to the at least one semiconductor chip 5, wherein the structure 2 comprises a surface located within an interior of the semiconductor device, and the surface comprises a groove 12; and a sensor 16 comprising an optical fibre 13 passing through the groove 12, wherein the sensor 16 is configured to sense a temperature of the at least one semiconductor chip 5.Type: ApplicationFiled: April 20, 2021Publication date: July 27, 2023Inventors: Yangang Wang, Bruno Cerqueira Rente Ribeiro, Paul Durnford Taylor, Robin Adam Simpson, Callum Tarr, Michael David Nicholson, Daniel Bell, Tong Sun, Kenneth Grattan, Matthias Fabian
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Patent number: 11709873Abstract: Techniques and systems are provided for predicting answers in response to one or more input queries. For instance, text from a corpus of text can be processed by a reader to generate one or multiple question and answer spaces. A question and answer space can include answerable questions and the answers associated with the questions (referred to as “question and answer pairs”). A query defining a question can be received (e.g., from a user input device) and processed by a retriever portion of the system. The retriever portion of the system can retrieve an answer to the question from the one or more pre-constructed question and answer spaces, and/or can determine an answer by comparing one or more answers retrieved from the one or more pre-constructed question and answer spaces to an answer generated by a retriever-reader system.Type: GrantFiled: January 13, 2020Date of Patent: July 25, 2023Assignee: Adobe Inc.Inventors: Jinfeng Xiao, Lidan Wang, Franck Dernoncourt, Trung Bui, Tong Sun
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Publication number: 20230230198Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that implement a neural network framework for interactive multi-round image generation from natural language inputs. Specifically, the disclosed systems provide an intelligent framework (i.e., a text-based interactive image generation model) that facilitates a multi-round image generation and editing workflow that comports with arbitrary input text and synchronous interaction. In particular embodiments, the disclosed systems utilize natural language feedback for conditioning a generative neural network that performs text-to-image generation and text-guided image modification. For example, the disclosed systems utilize a trained model to inject textual features from natural language feedback into a unified joint embedding space for generating text-informed style vectors. In turn, the disclosed systems can generate an image with semantically meaningful features that map to the natural language feedback.Type: ApplicationFiled: January 14, 2022Publication date: July 20, 2023Inventors: Ruiyi Zhang, Yufan Zhou, Christopher Tensmeyer, Jiuxiang Gu, Tong Yu, Tong Sun
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Patent number: 11661628Abstract: The present invention regards a variety of methods and compositions for whole genome amplification and whole transcriptome amplification. In a particular aspect of the present invention, there is a method of amplifying a genome comprising a library generation step followed by a library amplification step. In specific embodiments, the library generating step utilizes specific primer mixtures and a DNA polymerase, wherein the specific primer mixtures are designed to eliminate ability to self-hybridize and/or hybridize to other primers within a mixture but efficiently and frequently prime nucleic acid templates.Type: GrantFiled: August 10, 2017Date of Patent: May 30, 2023Assignee: Takara Bio USA, Inc.Inventors: Emmanuel Kamberov, Tong Sun, Eric Bruening, Jonathon H. Pinter, Irina Sleptsova, Takao Kurihara, Vladimir L. Makarov
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Publication number: 20230154221Abstract: The technology described includes methods for pretraining a document encoder model based on multimodal self cross-attention. One method includes receiving image data that encodes a set of pretraining documents. A set of sentences is extracted from the image data. A bounding box for each sentence is generated. For each sentence, a set of predicted features is generated by using an encoder machine-learning model. The encoder model performs cross-attention between a set of masked-textual features for the sentence and a set of masked-visual features for the sentence. The set of masked-textual features is based on a masking function and the sentence. The set of masked-visual features is based on the masking function and the corresponding bounding box. A document-encoder model is pretrained based on the set of predicted features for each sentence and pretraining tasks. The pretraining tasks includes masked sentence modeling, visual contrastive learning, or visual-language alignment.Type: ApplicationFiled: November 16, 2021Publication date: May 18, 2023Inventors: Jiuxiang Gu, Ani Nenkova Nenkova, Nikolaos Barmpalios, Vlad Ion Morariu, Tong Sun, Rajiv Bhawanji Jain, Jason wen yong Kuen, Handong Zhao
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Publication number: 20230117626Abstract: A convolution apparatus including a data memory, a matrix unknit-knit device, and a convolution operation device, a convolution method, a matrix unknit-knit device, and a matrix unknit-knit method are provided. The matrix unknit-knit device unknits a first matrix stored in the data memory into s*s second matrices (or knits the s*s second matrices into the first matrix), where s is greater than 1. Pixels in each of s*s subblocks in the first matrix serve one-to-one as pixels of the s*s second matrices. A convolution operation device unknits a convolution kernel of a convolution operation with a stride of s into s*s sub-kernels, uses any one of the sub-kernels to perform a convolution operation with a stride of 1 on one corresponding second matrix, and accumulates the operation results the second matrices as the operation result of performing the convolution operation with a stride of s on the first matrix.Type: ApplicationFiled: October 3, 2022Publication date: April 20, 2023Applicant: Shanghai Biren Technology Co.,LtdInventors: Hao SHU, Zhou HONG, Lin CHEN, Tong SUN, Zhu LIANG, ChengKun SUN
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Publication number: 20230059367Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate a natural language model that provides user-entity differential privacy. For example, in one or more embodiments, the disclosed systems sample sensitive data points from a natural language dataset. Using the sampled sensitive data points, the disclosed systems determine gradient values corresponding to the natural language model. Further, the disclosed systems generate noise for the natural language model. The disclosed systems generate parameters for the natural language model using the gradient values and the noise, facilitating simultaneous protection of the users and sensitive entities associated with the natural language dataset. In some implementations, the disclosed systems generate the natural language model through an iterative process (e.g., by iteratively modifying the parameters).Type: ApplicationFiled: August 9, 2021Publication date: February 23, 2023Inventors: Thi Kim Phung Lai, Tong Sun, Rajiv Jain, Nikolaos Barmpalios, Jiuxiang Gu, Franck Dernoncourt
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Patent number: 11544503Abstract: A domain alignment technique for cross-domain object detection tasks is introduced. During a preliminary pretraining phase, an object detection model is pretrained to detect objects in images associated with a source domain using a source dataset of images associated with the source domain. After completing the pretraining phase, a domain adaptation phase is performed using the source dataset and a target dataset to adapt the pretrained object detection model to detect objects in images associated with the target domain. The domain adaptation phase may involve the use of various domain alignment modules that, for example, perform multi-scale pixel/path alignment based on input feature maps or perform instance-level alignment based on input region proposals.Type: GrantFiled: May 27, 2020Date of Patent: January 3, 2023Assignee: Adobe Inc.Inventors: Christopher Tensmeyer, Vlad Ion Morariu, Varun Manjunatha, Tong Sun, Nikolaos Barmpalios, Kai Li, Handong Zhao, Curtis Wigington
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Publication number: 20220391768Abstract: Adapting a machine learning model to process data that differs from training data used to configure the model for a specified objective is described. A domain adaptation system trains the model to process new domain data that differs from a training data domain by using the model to generate a feature representation for the new domain data, which describes different content types included in the new domain data. The domain adaptation system then generates a probability distribution for each discrete region of the new domain data, which describes a likelihood of the region including different content described by the feature representation. The probability distribution is compared to ground truth information for the new domain data to determine a loss function, which is used to refine model parameters. After determining that model outputs achieve a threshold similarity to the ground truth information, the model is output as a domain-agnostic model.Type: ApplicationFiled: August 9, 2022Publication date: December 8, 2022Applicant: Adobe Inc.Inventors: Kai Li, Christopher Alan Tensmeyer, Curtis Michael Wigington, Handong Zhao, Nikolaos Barmpalios, Tong Sun, Varun Manjunatha, Vlad Ion Morariu
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Patent number: 11520974Abstract: Techniques are disclosed for sharing user markings between digital documents and corresponding physically printed documents. The sharing is facilitated using an Augmented Reality (AR) device, such as a smartphone or a tablet. The device streams images of a page of a book on a display. The device accesses a corresponding digital document that is a digital version of content printed on the book. In an example, the digital document has a digital user marking, e.g., a comment associated with a paragraph of the digital document, wherein a corresponding paragraph of the physical book lacks any such comment. When the device streams the images of the page of the book on the display, the device appends the digital comment on the paragraph of the page of the book within the image stream. Thus, the user can view the digital comment in the AR environment, while reading the physical book.Type: GrantFiled: March 30, 2020Date of Patent: December 6, 2022Assignee: Adobe Inc.Inventors: Tong Sun, Qi Sun, Jing Qian, Curtis Michael Wigington