475 results about "Content generation" patented technology

Methods and systems are described for imaging and content generation. During a road trip, a driver or passenger observes an object or scene from a vehicle. From a perspective of the driver or passenger, the object or scene flows out of view in a relatively short amount of time. Images and video of the object or scene are captured with cameras. A field of view is extended beyond what the driver or passenger can easily observe. The capture is configurable to focus on particular types of objects or scenes. Recordings of billboards and road signs are easily displayed after passing the object. Object identification, gaze determination, and interest determination are provided. Curated content is generated. Applications to extended reality environments are provided. Artificial intelligence systems, including neural networks, and models are utilized to improve the imaging and content generation. Related apparatuses, devices, techniques, and articles are also described.

This application belongs to the field of digital push technology and relates to a method and system for collaborative online and offline marketing content delivery, aiming to solve the problems of rigid delivery, low accuracy, and disconnect between online and offline in existing technologies. The method includes: acquiring user behavior characteristics and scenario characteristics collected by offline display terminals when displaying content, and determining interests; when preset conditions are met, sending an instruction to cause the offline display terminal to dynamically generate a unique interaction identifier and output an interaction entry point; receiving online access requests and extracting the unique interaction identifier from them, associating display events and online interaction events based on the unique interaction identifier to obtain event-level attribution results; and adjusting the generation control parameters and / or delivery strategy parameters of subsequent target marketing content based on the attribution results. This application can achieve event-level association and attribution between offline display and online interaction, forming a closed loop of content generation, display, interaction, and optimization, improving the efficiency of marketing content generation, delivery accuracy, and conversion effect.

This invention discloses an adaptive adjustment method for intelligent display equipment used in digital exhibitions, specifically relating to the field of digital exhibition technology. The method involves collecting multi-source data such as ambient light, visitor distribution, and sound through distributed lightweight sensor nodes; performing semantic fusion using a lightweight neural network to construct a dynamic exhibition hall context graph; instantiating an intelligent agent for each display device; generating resource scheduling proposals based on a shared reward mechanism and a multi-agent collaborative decision-making algorithm; an arbitrator detecting and resolving resource competition and effect offsetting conflicts; outputting a globally consistent set of control instructions; ensuring smooth execution of instructions by the devices; dynamically generating adapted display content based on contextual semantics; and continuously optimizing the decision-making model through online learning based on visitor behavior feedback. This invention achieves collaborative scheduling of equipment resources and adaptive content generation, improving the exhibition experience and resource utilization efficiency.

The application provides a kind of image region missing content generation method and system based on three-dimensional partial differential equation, according to the method of the application, comprising: obtaining the image to be completed and its related auxiliary information;The complete image after completion is obtained by inputting the image to be completed and the auxiliary information into the pre-constructed image generation network model;Wherein, the image generation network model is the progressive image region missing content generation network PDE-PINet constructed based on three-dimensional partial differential equation.The application proposes an image region missing content generation method based on three-dimensional partial differential equation network, which combines partial differential equation with rigorous mathematical basis and deep learning to achieve better image region missing content generation effect;At the same time, through the mathematical constraint of three-dimensional partial differential equation, the structural distortion problem caused by the dependence of traditional deep learning method on data driving is effectively solved, and the coherence of the overall structure of the image can still be effectively maintained in large-area missing region generation.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for content generation. One of the methods includes receiving user selected content at a user device, the content including a first content item and a second content item; presenting the first content item in region of a user interface of an application; detecting a first user interaction occurring within a specified area of the region; determining whether the first user interaction satisfies a threshold duration; in response to determining that the first user interaction satisfies the threshold duration, presenting the second content item in the region of the user interface in place of the first content item, the second content item being associated with the first content item.

Aspects of the present disclosure provide techniques for automated content generation in a brand voice through machine learning. Embodiments include determining brand voice attributes of a user of a software application based on data provided by the user, the brand voice attributes comprising a narrative brand voice description, one or more brand voice trait classifications, and one or more writing style attributes. Embodiments include generating, based on the determining of the brand voice attributes of the user, a prompt that instructs a generative language processing machine learning model to generate content according to the brand voice attributes of the user. Embodiments include providing the prompt to the generative language processing machine learning model. Embodiments include receiving the content from the generative language processing machine learning model in response to the prompt. Embodiments include outputting the content for display via a user interface. 20 25 20 14 94 28 F eb 2 02 5 2 7 A B S T R A C T 2 0 2 5 2 0 1 4 9 4 2 8 F e b 2 0 2 5 FIG. 1 100 SERVER 110 BRAND VOICE CONTENT GENERATION ENGINE 112 CLIENT 120 USER INTERFACE 122 CONTENT IN BRAND VOICE 126 NETWORK 150 REQUEST 124 EXTERNAL DATA SOURCE(S) 130 BRAND VOICE ATTRIBUTE DETERMINER 114 BRAND VOICE CONTENT GENERATOR 116 1 / 51 / 5 100 EXTERNAL DATA SOURCE(S) 130 SERVER 110 BRAND VOICE CONTENT GENERATION ENGINE 112 BRAND VOICE BRAND VOICE ATTRIBUTE CONTENT DETERMINER GENERATOR 114 116 NETWORK CONTENT IN REQUEST 150 BRAND VOICE124 126 CLIENT 120 USER INTERFACE 122 FIG. 1 20 25 20 14 94 28 F eb 2 02 5 1 0 0 2 0 2 5 2 0 1 4 9 4 2 8 F e b 2 0 2 5 B R A N D V O I C E C O N T E N T G E N E R A T I O N E N G I N E 1 1 2 N E T W O R K C O N T E N T I N C L I E N T 1 2 0

This invention relates to the field of teaching aids technology, and more particularly to a method for adaptive generation of speech content based on a multimodal large model and a real-time question-answering system. The method includes the following steps: acquiring multimodal raw materials provided by the speaker and parsing them using a multimodal large model to extract the speech's logical structure, key entities, and content attribute tags; organizing the multimodal large model parsing results into a content tree and constructing a knowledge graph representing arguments, sub-arguments, cases, data, and conclusions, wherein the knowledge graph defines support, exemplification, and comparison relationships between nodes; learning from the speaker's historical audio / video and text data and outputting a speaker style vector; generating an initial speech suite and configuring adjustment strategy templates, priority definitions, and safety boundaries. In this invention, by organizing content into an operable knowledge graph / content tree and constructing a real-time closed loop of "perception—understanding—decision—generation," dynamic path selection and content generation based on real-time multimodal perception are achieved.

Methods and systems for generating output content using a generative artificial intelligence (AI) model based on an input. A similarity-assessment layer at the output of the generative AI model determines a similarity measure for the output content vis-à-vis pre-existing items in a repository. The similarity measure is compared to a threshold value and, responsive to the comparison indicating excessive similarity, one or both of the input and the generative AI model are adjusted, and the generative AI model is re-run to generate new output content.

This invention discloses a method, system, device, and medium for generating and presenting a large-scale modular fact-checking response. The method includes: acquiring user input instructions and decomposing them into information fragments to be checked; retrieving and aggregating evidence sets from a pre-set knowledge base or online information sources; determining the consistency of the information fragments based on the evidence, and outputting the verification conclusion and confidence level; determining the risk level and generating control parameters according to a pre-set risk assessment strategy; and using the control parameters to control or adjust the generation and / or perceptual presentation of the response content. The control or adjustment methods include constraints during generation and post-processing corrections to suppress deterministic assertions and output uncertainty identifiers and evidence summaries when evidence is insufficient or conflicting. This solution improves factual consistency and traceability through decoupling of responsibilities and an auditable evidence chain, and reduces the risk of illusion caused by consistency overfitting. The risk level can be further mapped to decoding parameters of the generation module (such as temperature, top-p, and logit bias masks) or modulation parameters of the perceptual presentation. The response data can be provided to the client via a network interface, allowing the client to control the output presentation.

This invention discloses a secure voice-based intelligent customer service system and interaction method based on a multi-agent architecture. The system includes an ASR (Automatic Speech Recognition) module, multi-layered security barriers, a main retrieval agent, a specialized retrieval agent cluster, a parallel retrieval and result aggregation module, an LLM (Limited Language Modeling) synthesis engine, and a TTS (Text-to-Speech) module. Through multi-agent system architecture and methodological design, this invention achieves modular processing, parallel retrieval tasks, and closed-loop security control. By enabling independent calls between input, output, agents, and inference stages via multi-layered security barriers, the system effectively mitigates risks such as prompt word injection, indirect injection attacks, harmful content generation, and information leakage. Sensitive information identification, access permission verification, and content compliance review are embedded in each stage of input, retrieval, information synthesis, and output to prevent sensitive data leakage and meet the application requirements of high-security business scenarios (such as finance, telecommunications, and government services).

The present application relates to the technical field of artificial intelligence, and more particularly to an AIGC content generation method and system based on a brand knowledge base. The method comprises: obtaining a content generation request carrying a brand identifier and a domain identifier; extracting brand knowledge units from multiple brand knowledge bases according to the brand identifier; identifying the knowledge coverage density of each knowledge base on the domain identifier through domain coverage range annotation; marking the knowledge sources with a coverage density lower than a preset benchmark as sparse knowledge sources, and marking the knowledge sources not lower than the benchmark as dense knowledge sources; taking the knowledge fragment with the nearest neighbor semantics to the domain identifier in the dense knowledge source as an anchor point, performing cross-knowledge migration completion on the sparse knowledge sources, and generating the completed sparse knowledge units by remapping the style of the anchor point brand tone constraint according to the audience portrait of the sparse knowledge sources; and outputting a content generation strategy bound with the brand identifier and the domain identifier.

This invention relates to the field of artificial intelligence application technology, specifically to a method and system for automatically delivering AI-generated content to a target computer application, comprising the following steps: S100, responding to a natural language command input by a user on a first terminal, acquiring target text content generated by a large language model, and providing editing and confirmation operations for the target text content in the interactive interface of the first terminal; This invention constructs an end-to-end delivery solution from AI content generation to automatic filling of target applications by organically integrating a large language model, computer vision positioning, and underlying USBHID device simulation technology. This solution relies on a hardware bridging module as a standard peripheral to access the target computer, achieving high compatibility across operating systems without the need to install any customized software or drivers, and ensuring the system security of the target device.

This application relates to an interactive method, apparatus, computer device, computer-readable storage medium, and computer program product. The method includes: displaying a content display page containing target display content and associated interactive entry points; obtaining interactive material content and the target display content based on the associated interactive entry points; wherein the interactive material content is multimedia material content selected by interactive participants for participation in the interaction; generating associated interactive content based on the interactive material content and the target display content; and publishing comments on the target display content according to the associated interactive content. Using this method, the associated interactive content and the original target display content can be avoided from being disconnected, improving the relevance and interactive effect of the comment interaction.

The application relates to the technical field of natural language processing, can be applied to the creation content generation scene of financial technology and medical health, and discloses a creation content generation method, device, equipment and storage medium. A user initial creation requirement is received, and a structured core creation demand is extracted based on a preconfigured understanding instruction; a content first draft, a guiding question and a multi-modal prompt word are synchronously generated based on a preconfigured generation instruction, the content first draft and the guiding question are pushed to the user; user feedback information is received, knowledge demand is analyzed based on a preconfigured analysis instruction and an optimization instruction, and matched professional information is called from a preset knowledge base, a revised text is generated in combination with the feedback information and the content first draft; multi-modal content with semantic alignment is generated based on the multi-modal prompt word and the revised text, and the revised text and the multi-modal content are integrated and pushed to the user. The application realizes high-quality, personalized and automatic generation of creation content through preconfigured exclusive instructions in the whole process.

This invention discloses a method, apparatus, device, and medium for generating video webpage playback data. The method includes: acquiring at least one video resource and webpage document content of a target video webpage; when interactive video resources exist, generating a webpage data packet of the target webpage type based on each video resource and the webpage document content; the webpage data packet is used to load onto the webpage of the target webpage type; when no interactive video resources exist, reconstructing each video resource based on the webpage document content to obtain at least one material unit and corresponding loading configuration information; generating resource loading data based on each material unit and the corresponding loading configuration information; and parsing and loading the resource loading data through a native video application on the client side. This invention can save network transmission resources and improve compatibility.

This invention discloses an AI-interactive AR (Augmented Reality) cultural wall system for cultural tourism, belonging to the field of AR system technology. The surface of the cultural wall is equipped with a pre-embedded feature set, including visual markers, differentiated texture features, 3D depth variation areas, and specifically designed interactive hotspots. These features provide the system with stable visual benchmarks, semantic distinction criteria, depth cues, and precise positioning anchors. The system includes: a feature point acquisition module, used to collect the feature set on the cultural wall through a multimodal feature extraction algorithm to construct a 3D spatial map with semantic annotations; a user positioning and pose estimation module; an AI content generation engine; and a spatial adaptation and rendering module. Through the cultural wall feature set and the multi-module collaborative system, precise spatial integration of virtual content and the physical wall surface is achieved, along with intelligent dynamic content generation based on user behavior, effectively enhancing the immersion, interactivity, and personalization of the AR cultural experience.

An electronic device according to one embodiment in the present document may comprise: one or more microphones; one or more cameras; at least one processor; and a memory for storing instructions. When executed by the at least one processor, the instructions can instruct the electronic device to: detect an event to be recorded while collecting activity-related data of a user; record, in response to the detection of the event, activity information acquired from the one or more microphones and / or the one or more cameras for a designated period of time; determine, on the basis of the activity-related data, whether a content generation condition is satisfied; determine a content generation item for producing media content if the content generation condition is satisfied; and combine at least some pieces of the recorded activity information on the basis of the determined content generation item so as to generate the media content. Other various embodiments identified through the present document are possible.

The application provides a water conservancy and hydropower construction scheme generation method based on construction object feature modeling, comprising the following steps: step 1) construction object feature identification and modeling; step 2) construction scheme generation constraint construction: combining engineering specifications, historical schemes, expert experience and other data, a set of multiple source heterogeneous constraint conditions is constructed, and the set of constraint conditions is in a structured form to participate in the combination and generation of subsequent construction scheme content; step 3) combination and generation of construction scheme content: the construction scheme is disassembled into multiple controllable content units, and combination and generation are performed according to different constraint conditions in the generation process. The method adopts a content generation mechanism of "constraint driving + content combination", realizes unified support of a set of technical schemes for multiple construction scenes, and significantly improves the application range of the technical scheme.

The application discloses a railway foreign matter intrusion recognition decision method and device, equipment and medium, relates to the image recognition technical field, and includes: through collecting and preprocessing the inspection image, obtaining the foreign matter category and position information through the lightweight detection model, relying on the two types of information to quantify the risk level, fusing multiple information to construct a query vector, and calling regulations from the railway knowledge graph with the help of a search enhancement generation framework, and generating standard disposal suggestions combined with the search content. Through the coupling of the risk matrix and the knowledge graph, a closed loop from perception to decision is realized, and the accuracy and compliance of foreign matter disposal are improved.

This invention provides a method and apparatus for generating vocabulary memorization content, relating to the field of data processing technology. The method includes: acquiring multidimensional feature data of a target word to be memorized and a target user; wherein the multidimensional feature data includes at least the target user's personalized image features and learning stage identifier; constructing a target scene corpus based on the semantic information of the target word to be memorized; constructing structured prompt information for driving a generative model based on the target word to be memorized, the target scene corpus, and the multidimensional feature data; inputting the structured prompt information into a pre-trained generative artificial intelligence model to generate a dynamic mnemonic comic, and displaying the dynamic mnemonic comic on a terminal device; wherein the dynamic mnemonic comic includes a character image generated based on the personalized image features, and the character image interprets the meaning of the target word to be memorized within the context defined by the target scene corpus.

This invention relates to a content generation method and related equipment. The method involves acquiring source information, aligning and integrating the source information temporally based on a unified timeline to obtain fused information, and constructing structured data based on the fused information. Based on a preset thought chain and the structured data, prompt words are generated. These prompt words are then input into a vertical domain large-scale model and a large-scale language model to generate first content and second content, respectively. The first and second content are evaluated, and either the first or second content is selected as the target content based on the evaluation results. In application scenarios such as generating summaries that capture the core highlights of a live stream, or generating interactive dialogue for a live stream, this method can efficiently and accurately perform automated semantic understanding and content (summary or interactive dialogue) generation for live stream content.

We provide the system. [Solution] A data collection means for receiving environmental and biometric information obtained from the user, An analysis means analyzes the data received from the data collection means and determines the user's state, Content generation means that generates virtual reality content based on the user's state determined by the analysis means, A means for transmitting generated virtual reality content to users, An adaptive mechanism that receives user interaction and dynamically adjusts content based on it, A means that enables the generation of virtual reality content related to the surrounding physical environment based on location information, A system that includes this.

Some aspects relate to technologies for generating and validating content providing summary information for parts on a listing platform, such as compatibility information and item characteristic information for the parts. In some aspects, input data comprising attribute-value pairs based on one or more items is accessed for content generation. The input data and one or more pre-defined generation prompts are provided to a first generative model, which generates content comprising natural language text as output. In some aspects, the content is validated by providing the content and one or more pre-defined validation prompts to a second generative model. If approved, the content can be provided for presentation on a user device. If rejected, the content is not provided for presentation. In further aspects, the rejected content is used by a third generative model for tuning the pre-defined generation prompts.

The application provides a training method and a content generation method, device and equipment of a question and answer model. The method comprises: obtaining sample question content; based on a plurality of reasoning strategies, outputting answer content corresponding to each reasoning strategy through a question and answer model; assigning a reward value to each answer content, the reward value comprising an adaptive reward value, wherein the higher the adaptive reward value is, the more the answer content is correct and the more the corresponding reasoning strategy meets the reasoning requirement; and adjusting the model parameters of the question and answer model based on the reward value of each answer content. Through the reinforcement learning mechanism, the question and answer model can autonomously learn to select a reasoning strategy that can ensure the correctness of the answer content and better meet the reasoning requirement according to the question content, thereby improving the efficiency of the question and answer model while ensuring the accuracy of the question and answer model.

The application discloses a kind of AIGC content generation and GEO optimization distribution method and system based on knowledge graph constraint.The core of the method is to change the AIGC content generation process from "unconstrained free generation" to "knowledge graph hard constraint generation", and change the content distribution from "passive waiting for inclusion" to "active reverse optimization distribution".The method first establishes the brand exclusive text business travel structured knowledge graph, and uses the hard facts such as merchant coordinates, joint IP and product SKU as mandatory boundary prompt words to constrain the text generation of large language model;At the same time, through the reverse analysis of the recommendation preference of mainstream generative AI engine by automatic probe, the preference vector matrix is formed to guide corpus generation;Then, through the full-automatic distribution platform, the corpus is fed to the whole network in batches through multiple channels;Finally, through the inclusion tracking probe and feedback closed-loop mechanism, the dynamic rectification of strategy is realized.The application realizes the generative engine optimization (GEO) for large model for the first time at the system level, effectively eliminates AI content illusion, realizes more than 80% automation of core operation process, and significantly reduces the cost of enterprise customer acquisition.

This invention relates to the field of content generation technology, and particularly to a method, apparatus, device, and storage medium for generating interactive content in museums. The method parses multimodal information to obtain scene recognition information, matches it with a spatial semantic map to obtain exhibit categories, dynamically updates interest preference vectors based on exhibit categories and acquired multimodal behavioral data to generate dynamic visitor profiles, generates multimodal guided tour content through association reasoning based on exhibit categories, and obtains a sharing index based on multimodal behavioral data and dynamic visitor profiles using a sharing willingness assessment model. If the index exceeds a sharing threshold, materials are selected to generate content to be shared. This method solves the problems of fragmented interactive experience and inefficient sharing generation in existing guided tour modes, reduces the manpower and content operation costs of museum guides, provides technical support for upgrading the museum visitor experience and efficiently disseminating culture, and is applicable to intelligent guided tours and interactive content generation in various cultural and museum venues.

The application provides a kind of legal judgment result prediction intelligent feedback error correction method and electronic equipment, including the secretary intelligent agent obtained by the training of large language model, the prosecution intelligent agent, the defense intelligent agent and the judge intelligent agent of sentencing, method includes: through secretary intelligent agent, event-level disassembly and extraction are carried out to case fact text, and fact atom set is obtained;Through the prosecution intelligent agent, the charge set is generated based on fact atom set, and through the defense intelligent agent, the refutation set is generated based on fact atom set;Through the judge intelligent agent of sentencing, the charge set and the refutation set are carried out to confrontation type collaborative reasoning, and initial sentencing result is obtained;The initial sentencing result is checked, if there is doubt charge, then the prosecution intelligent agent and the defense intelligent agent are used to generate correction content for doubt charge;Through the judge intelligent agent of sentencing, the final sentencing result is generated according to the correction content.Can assist judicial organ to realize more stable, interpretable and efficient legal judgment prediction.

Implementations disclosed herein are directed to generative model (GM) reasoning that generates image(s) / video(s) as part of a chain-of-thought (CoT) in response to receiving certain user inputs that do not request any generative image content and / or generative video content. Processor(s) of a system can: receive user input, generate responsive content that is responsive to the user input, and cause the responsive content to be rendered. In generating the responsive content, the processor(s) can process, using the GM input, initial GM input to generate initial GM output, the initial GM input including at least the user input, and the initial GM output including at least a generative / video. In generating the responsive content, the processor(s) can further determine, based on processing at least the generative image / video, the responsive content. Thus, the processor(s) can generate the image(s) / video(s) to reason about the user input and / or the responsive content in these modalities.

To provide a technology for presenting, in content generated by a generative model, the regions generated by the generative model and / or regions presumed to have been generated by the generative model, in a more intuitive way. [Solution] In content generated by a generative model, the regions generated by the generative model and / or regions that are presumed to have been generated by the generative model are detected based on information related to content generation, and the detected regions are presented.