339 results about "Multiple context" patented technology

A method of generating outputs in LLMs including receiving including textual content, defining a context for the documents including identifying a topic or a category, segmenting the textual content into content chunks associated with the topic or category, assigning a tag to each content chunk, identifying selected chunks, adding metadata to the selected chunks indexing the selected chunks, receiving a query, and performing a response generation process including determining if a cache includes information for the query and either retrieving the information from the cache or performing a search of the index to retrieve the information, generating an augmented query by augmenting the query with retrieved information, generating a response from the augmented query, evaluating the response for compliance with criteria, and one of generating a final response and transmitting the final response to the user or performing a fine-tuning process comprising redefining the of the one or more contexts.

A computing system receives a prompt to be provided as input to a large language model. The computing system generates generating an input string to the large language model by appending a plurality of contexts to the prompt. The plurality of contexts defines rules for the large language model to follow when generating the prompt. The plurality of contexts includes a negative context. Based on the prompt and the plurality of contexts, the computing system generates an attention matrix representing relationships between the prompt and the plurality of contexts. The computing system provides the attention matrix to a trained neural network to determine a likelihood that the prompt is malicious. Responsive to determining that the prompt is likely a malicious prompt, the computing system initiates a remedial action.

An adaptive data system (ADS) for cognitive data processing is disclosed. The ADS includes an adaptive semantic preprocessor, a trigger detector, a temporal batching engine, a symbolic encoder, and a dynamic cognitive transformer engine. The adaptive semantic preprocessor is configured to receive input data from one or more databases and identify cognitive data attributes comprising one or more contextual, semantic, and temporal attributes from the received input data. The trigger detector is configured to identify semantic divergence of the identified cognitive data attributes and provide a standardized data. The temporal batching engine is configured to provide a high-dimensional cognitive data from the standardized data. The symbolic encoder compresses the high-dimensional cognitive data. The dynamic cognitive transformer engine is configured to determine decision making rules, analyze the compressed high-dimensional cognitive data based on the decision making rules and provide recommendations based on an outcome of the analysis to a user.

A method is described. The method comprises: extracting one or more contents related to an organization from one or more data sources based on one or more job role names and one or more contextual inputs; determining, using an artificial intelligence engine, at least one of an organizational structure, one or more roles, one or more responsibilities, one or more hierarchical relationships, one or more access levels, one or more service actions, and one or more departments of the organization from the one or more contents; and generating, using the artificial intelligence engine, one or more job descriptions based on at least one of the organizational structure, the one or more roles, the one or more responsibilities, the one or more hierarchical relationships, the one or more access levels, the one or more service actions, and the one or more departments.

In certain examples, computer-implemented methods include assembling automatically generated content into a website structure that is optimal to a particular user and tailored to user goals and consistent with attributes of media assets of the user. The method further includes: analyzing, for the particular user (e.g., individual or entity), inputs and media assets; constructing a set of context-aware prompts, wherein each of the context-aware prompts is associated with one or more contexts discerned in response to user inputs and media assets being analyzed; and generating, via large language modeling and based on the constructed context-aware prompts, the website content inclusive of text, code, and media elements. In photography examples, such methods customize content based on responses to constructed context-aware prompts, and use a library of predefined website content (e.g., images) with configurable parameters and customized content created dynamically.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating descriptions of digital components. In one aspect, a method includes receiving data indicating a query received from a client device of a user. An initial digital component is obtained. Search history data that includes a set of related past queries received from the user is obtained. Updated text related to the first resource is generated by conditioning a language model with one or more contextual inputs that cause the language model to generate one or more outputs that include the updated text, the one or more contextual inputs characterizing one or more of the first query, data related to the initial digital component, the sequence of related past queries, or one or more tasks to be performed by the language model. An updated digital component that depicts the updated text is generated and provided.

A method for enhancing data security includes receiving data. The method includes obtaining a plurality of contextual factors associated with the data. The further method includes determining an encryption level based on at least one of the contextual factors. The method further includes determining a type of encryption based on the encryption level. The method further includes encrypting the data using the type of encryption to generate encrypted data. The method further includes associating an access control level with the encrypted data to generate associated encrypted data. The method also includes determining a storage location for the associated encrypted data based on the encryption level, wherein determining the storage location is based on a data sensitivity associated with the data or a compliance rule. The method further includes sending the associated encrypted data to the storage location.

An example operation may include one or more of receiving interaction content from a communication session between a source device and a service provider device of a service provider, identifying a plurality of contextual attributes of the communication session based on execution of at least one large language models (LLMs) on the interaction content, converting the interaction content and the plurality of contextual attributes of the communication session into vectorized data based on execution of an additional LLM, labelling the vectorized data with identifiers of the plurality of contextual attributes, and storing the vectorized data within a vector database.

The invention discloses an image colorization method, system and device based on double-branch interactive fusion. The method relates to the technical field of image processing, and comprises the following steps: preprocessing collected original data; extracting local spatial information and global semantic information from the processed original data by adopting a local feature extraction branch and a global feature extraction branch; combining the features extracted by the local feature extraction branch and the global feature extraction branch by adopting an interactive fusion module; a plurality of stacked context aggregation modules are adopted to perform complementary fusion among the features output by the local feature extraction branch, the global feature extraction branch and the interactive fusion module; designing a loss function, and minimizing the loss function of the network output image and the label; according to the method, a local feature extraction branch and a global feature extraction branch are provided, and an interactive fusion module and a context aggregation module are combined, so that the aggregation capability of multi-scale context semantic features is enhanced, and the boundary definition and detail expressive force of a colorization result are optimized.

A system comprises an array of reconfigurable units including a plurality of pattern compute units (PCUs) and a plurality of pattern memory units (PMUs), and a compiler configured to receive a tensor including a plurality of memory access patterns of a first type (read) and a second type (write) located in a logical memory of the compiler. Each memory access pattern includes a memory access particular to that type. The compiler is configured to create a plurality of duplicates of the tensor and assign one or more contexts of any type to the duplicate tensors, such that no two contexts of the same type are in the same duplicate tensor. The compiler is configured to trim the duplicate tensors to retain portions including its corresponding assigned contexts remove portions that are inconsequential to the assigned contexts and dispatch the assigned contexts from each duplicate tensor to one or more PMUs.

Aspects of the disclosure are directed to automatic prompt generation based on a meeting discussion. A live transcript of a virtual meeting is obtained while a virtual meeting is being conducted. The live transcript includes current content discussed by participants of the virtual meeting. A determination is made based on the live transcript of whether the current content indicates a request of a participant for an operation to be performed with respect to the virtual meeting. Responsive to a determination that the current content indicates the request of the participant for the operation, one or more of a context or a sentiment associated with the request is identified. A prompt for an artificial intelligence (AI) model is generated based on the request and the one or more of the context or the sentiment. The AI model is trained to perform the operation with respect to the virtual meeting.

The invention discloses an AI-based vulnerability repair rule generation method and related equipment, and relates to the field of electric digital data processing. A computer device performs double analysis on a vulnerability code snippet and a vulnerability description text through a large language model, constructs double representation of an abstract syntax tree and a semantic graph, and performs cross-modal alignment on the semantic graph and the abstract syntax tree to obtain a vulnerability context relationship matrix. And the computer device traverses the abstract syntax tree, extracts vulnerability code feature vectors, and determines a plurality of repair modes according to vulnerability type identifiers. And the computer equipment calculates the similarity between the vulnerability code feature vector and a plurality of context constraint conditions, screens a target repair mode, performs feasibility verification on the target repair mode based on the vulnerability context relation matrix, and determines an optimal repair mode, thereby generating a repair rule. The double analysis and cross-modal alignment mode greatly improves the accuracy and reliability of vulnerability repair rule generation.

The present disclosure relates to cybersecurity architectures and systems for assessing and quantifying security threats and risks associated with machine-readable codes, such as quick response codes, barcodes, data matrix codes, and other types of codes. A security application comprises a multi-context threat assessment system configured to analyze a broad spectrum of risk assessment attributes across multiple contexts. These contexts relate to the machine-readable code itself, target network resources identified by the code, entities affiliated with the code, end-users interacting with the code, and enterprise systems policies. The system can evaluate various risk assessment attributes for each of these contexts to more accurately quantify potential security risks associated with the machine-readable codes. The security application further includes an API for extending its threat assessment capabilities to various digital ecosystems and an AI-powered learning network comprising language models and computer vision systems to enhance threat detection and risk quantification capabilities.

A multi-channel ticket creation and service management system that includes: a graphical interface controller configured to provide a graphical user interface (GUI) accessible through a plurality of predefined Uniform Resource Locators (URLs), the GUI including interactive service request forms associated with a plurality of hierarchical service and subservice classifications; a form processing circuit operatively coupled to the graphical interface controller and configured to receive a selected service-subservice combination from a user and dynamically populate subsequent input fields based on a predefined service taxonomy, the input fields including contact information, email address, subject, location identifier, area of ​​responsibility field, and a description field; a rule execution logical processing unit coupled to the form processing circuitry, the rule execution logical processing unit configured to enable or disable one or more context-sensitive fields based on logical rules stored in a service-subservice dependency tree, the logical rules governing the enablement of date and time fields exclusively when the selected service is journalism and the selected subservice is newspaper reporting; an authentication mapping processor comprising a session parser and a user-to-department resolver, wherein the session parser is configured to extract user credentials and associated metadata from session cookies or authentication tokens, and the user-to-department resolver is configured to auto-populate an activity-driven scope field based on the extracted metadata and an organizational mapping scheme; and a validation and transmission control unit configured to check the completeness and data type conformity of all enabled fields, generate a structured ticket record, and transmit it to a central ticket management platform.

The invention provides a code review model training method, device and equipment, and a code review method, device and equipment, and the code review model training method comprises the steps: obtaining a training sample which comprises a sample code and review information of the sample code; a retrieval sub-model in the pre-training code review model is utilized to retrieve the sample code, multiple pieces of context information are obtained, and different pieces of context information correspond to different retrieval ranges; combining the plurality of pieces of context information with the sample code to obtain a plurality of pieces of prompt information; generating initial review information of the multiple pieces of prompt information by utilizing a generation sub-model in the pre-training code review model; selecting output review information from the multiple pieces of initial review information; and based on the difference between the output review information and the review information of the sample code, optimizing model parameters of the pre-trained code review model to obtain a trained code review model. The context understanding capability of the model can be enhanced, and the understanding of the model on complex codes is improved.

Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and / or the like for retrieving a subgraph that is used to generate one or more answer outputs responsive to an input query by: (i) generating one or more context embeddings that are associated with an input query, (ii) identifying one or more candidate node paths and one or more node relations based on a knowledge graph, (iii) identifying, using a predictive machine learning model, one or more context-relationship rankings based on the one or more candidate node paths, the one or more node relations, and the one or more context embeddings, and (iv) generating one or more subgraph data objects based on the one or more context-relationship rankings.

The invention discloses a power industry dynamic knowledge base construction method and system based on a large language model, and relates to the field of electric digital data processing, and the method comprises the steps: receiving a power field document imported by a user, and converting the power field document into an electronic document; calling a large language model to analyze the electronic document, extracting a terminology definition, chart position information and a document logic level in the electronic document, and generating a knowledge unit containing a plurality of contexts; connecting the knowledge units into directed knowledge links, calculating semantic similarity between adjacent knowledge units in the directed knowledge links, and segmenting the directed knowledge links to obtain a plurality of knowledge topics; receiving a knowledge retrieval instruction, and determining a target knowledge theme corresponding to the knowledge retrieval instruction; and extracting a corresponding target knowledge unit in the target knowledge theme, and generating a knowledge retrieval result based on a target context of the target knowledge unit. By implementing the method, knowledge base construction can be optimized, and the integrity of knowledge base data is ensured.

Techniques are described with respect to a system, method, and computer program product for dynamically creating virtual learning environments. An associated method includes analyzing plurality of users associated with a virtual environment; determining a plurality of contextual information based on respective geographic locations of the plurality of users; and adjusting the virtual environment based on the determination; wherein adjusting comprises monitoring a plurality of interactions of the plurality of users with the virtual environment based on the plurality of contextual information.

A method may include transmitting, to a management service producer, a first request to create a set of clusters and to train a machine learning model for one or more clusters in the set of clusters for a plurality of contexts. The method may also include transmitting, to the management service producer, a second request to dynamically monitor the set of clusters. The method may further include receiving, after at least one of the first request or the second request, cluster reports from the management service producer as a result of creation of the set of clusters. The method may also include receiving, after at least one of the first request or the second request, training reports from the management service producer as a result of dynamic monitoring of the set of clusters, and training of the machine learning model.

A system uses a contextual bandit model for query processing. The system receives, from a client device, a user query for identifying one or more items by the system. The user query is described by one or more query features. The system obtains one or more contextual features describing a context of the user query. The system applies a contextual bandit model to the query features and the contextual features to select a query processing model from a plurality of query processing models. The system applies the selected query processing model to the user query to obtain query results. The system transmits the query results for display on the client device.

Media, methods, and systems are provided for contextual automation within a group-based communication system using buttons persisted within a virtual space of the group-based communication system. The buttons are configured to initiate one or more workflows that perform one or more external or internal operations contextually based on one or more contextual parameters associated with the buttons. When actuated, the buttons call a specific workflow and pass the one or more contextual parameters to the workflow.

A system and method for adapting one or more cybersecurity microservices to accelerate cybersecurity threat mitigation includes constructing a subscriber-specific data corpus comprising a plurality of distinct pieces of computing environment-informative data of a target subscriber; adapting a subscriber-agnostic microservice of the cybersecurity service to a subscriber-specific microservice, wherein: the subscriber-agnostic microservice includes a plurality of subscriber-agnostic cybersecurity event handling instructions, and adapting the subscriber-agnostic microservice to the subscriber-specific microservice includes generating a plurality of context-informed cybersecurity event handling instructions; augmenting the subscriber-agnostic microservice to include the plurality of context-informed cybersecurity event handling instructions; computing for a target cybersecurity event a subscriber-specific threat severity level based on one or more of the plurality of context-informed cybersecurity event handling instructions; executing, by one or more computers, a threat mitigation action or threat disposal action based on the computing of the subscriber-specific threat severity level for the target cybersecurity event.

A method, system, and computer program product for contextually calibrating quantum hardware. One or more contextual calibrations are selected or identified to minimize a contextual cost function of a quantum circuit. Examples of such contextual calibrations include, but are not limited to, tuning the amplitude, tuning the frequency duration, tuning the envelopes, recalibrating the error correction for specific qubits, recalibrating the measurement discriminator (identifies the specific quantum state), etc. The quantum hardware used to perform an execution of the quantum circuit may then be calibrated using the selected or identified contextual calibration(s). By minimizing the contextual cost function, such as via specific calibrations (e.g., tuning frequency duration, tuning amplitude), the performance of a general quantum device for a particular quantum circuit can be improved. For example, such contextual calibrations, such as at runtime, reduce the quantum device noise under different operating conditions thereby improving device performance.

The invention discloses a context poisoning attack defense method oriented to an RAG application, and relates to the technical field of RAG. the method comprises the following steps: inputting a target query statement, and retrieving the target query statement to obtain multiple pieces of context information; taking representative sentences in the retrieved context information, and identifying and filtering potential malicious template clusters; the big language model gives all candidate answers according to existing context information, the logarithmic probability of all contexts to different candidate answers is calculated, and after the influence of parameter knowledge of the big language model is removed from the logarithmic probability, the support degree of all contexts to different candidate answers is obtained; the whole logarithmic probability vector is used as a support degree distribution condition of the context to the candidate answers; identifying a single piece of harmful information from the support degree distribution condition of the context to the candidate answers through a logistic regression model so as to filter wrong answers; according to the attack defense method provided by the invention, centralized injection of multiple malicious texts and sparse injection of a small number of malicious texts can be defended.

Systems and methods are described for contextualizing a simulated phishing communication based at least on one of language and locale. Initially, a template for a simulated phishing communication is created with content in a source language. Then one or more contextual parameters for a user are identified. The one or more contextual parameters identify at least one of a target language and a target locale. The content of the simulated phishing communication is modified according to at least one of the target language and the target locale and the simulated phishing communication is communicated to one or more devices of the user with the content modified for at least one of the target language and the target locale.

An example method performed by a Wireless Transmit / Receive Unit (WTRU) is described. The method comprises determining context information for execution of an edge-assisted task associated with a machine-type-communications (MTC) application, sending the context information, receiving one or more context-aware parameters and information related to usage of the one or more context-aware parameters, determining a configuration for at least one of an application layer or an upper network (NW) layer based on the received information, and sending a first uplink (UL) transmission using the one or more context-aware parameters for the application layer or the upper NW layer based on the determined configuration. The context information may indicate one or more of performance of the MTC application or performance of the edge-assisted task.

The invention discloses a visual Token compression method and device based on double-path fusion, and the method comprises the steps: obtaining an initial visual Token through employing a visual encoder; obtaining a learnable query vector, and adopting an attention mechanism to enable the learnable query vector to interact with the initial visual Token to obtain a plurality of context Token; analyzing a self-attention map of the initial visual Token in the visual encoder, so as to screen out a plurality of detail Token according to the self-attention map; obtaining a text prompt Token, and calculating a task correlation score of each detail Token by taking the text prompt Token and the plurality of context Token as a query; dynamically filtering or weighting the plurality of details Token according to the task correlation score to obtain a plurality of filtered details Token; the plurality of filtered detail Tokens are spliced with the plurality of context Tokens, so that a compressed visual Token can be obtained; therefore, the key global and local visual information can be intelligently reserved while the high compression ratio is realized and the calculation cost is reduced.

A computer implemented method for managing and remediating security drift in a public cloud network is disclosed. A security drift event may be received at a contextual impact classification engine of a server. An impact tier for the received security drift event may be assigned at the contextual impact classification engine. A queue shaping orchestrator at the server may reorder a queue with entries that include the received security drift event based on the assigned impact tier. A remediation engine of the server may determine a remediation for the received security drift event based on the assigned impact tier, and / or one or more contextual inputs received by the server.

A system comprises an image signal processor (ISP). The ISP is a discrete hardware unit and includes a line buffer, a memory controller, and one or more image processors. The memory controller is configured to allocate blocks within the line buffer to a plurality of contexts, and for each of the contexts: receive one or more lines of image data associated with a respective context and store the one or more lines of the image data associated with the context in a respective block allocated to the respective context. The one or more image processors of the ISP are configured to, for each respective context of the plurality of contexts, process the one or more lines of the image data associated with the respective context that are stored in the line buffer.