G06F40/00

PARAMETER UTILIZATION FOR LANGUAGE PRE-TRAINING

Embodiments are directed to pre-training a transformer model using more parameters for sophisticated patterns (PSP++). The transformer model is divided into a held-out model and a main model. A forward pass and a backward pass are performed on the held-out model, where the forward pass determines self-attention hidden states of the held-out model and the backward pass determines loss of the held-out model. A forward pass on the main model is performed to determine a self-attention hidden states of the main model. The self-attention hidden states of the main model are concatenated with the self-attention hidden states of the held-out model. A backward pass is performed on the main model to determine a loss of the main model. The parameters of the held-out model are updated to reflect the loss of the held-out model and parameters of the main model are updated to reflect the loss of the main model.

PARAMETER UTILIZATION FOR LANGUAGE PRE-TRAINING

Embodiments are directed to pre-training a transformer model using more parameters for sophisticated patterns (PSP++). The transformer model is divided into a held-out model and a main model. A forward pass and a backward pass are performed on the held-out model, where the forward pass determines self-attention hidden states of the held-out model and the backward pass determines loss of the held-out model. A forward pass on the main model is performed to determine a self-attention hidden states of the main model. The self-attention hidden states of the main model are concatenated with the self-attention hidden states of the held-out model. A backward pass is performed on the main model to determine a loss of the main model. The parameters of the held-out model are updated to reflect the loss of the held-out model and parameters of the main model are updated to reflect the loss of the main model.

APPARATUS AND METHOD FOR GENERATING A SCHEMA

An apparatus and method for generating a schema, the apparatus comprising at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to display, at a graphical control interface, a content field window, receive, as a function of the content field window, a criterion element, and generate a schema as a function of the criterion element.

Systems and methods for the comparison of selected text
11514226 · 2022-11-29 · ·

Systems and methods are disclosed for comparing selections of text to show differences between the two selections. The text may be selected from the same source or from two different sources. In one implementation, a system receives a first selection of text for comparison and places the selection in a first buffer. The system receives a second selection of text for comparison and places the second selection in a second buffer. The system compares the first buffer and the second buffer to determine differences and displays the differences. In some embodiments, the system may allow a user to choose two buffers from among a plurality of buffers for comparison.

Systems and methods for the comparison of selected text
11514226 · 2022-11-29 · ·

Systems and methods are disclosed for comparing selections of text to show differences between the two selections. The text may be selected from the same source or from two different sources. In one implementation, a system receives a first selection of text for comparison and places the selection in a first buffer. The system receives a second selection of text for comparison and places the second selection in a second buffer. The system compares the first buffer and the second buffer to determine differences and displays the differences. In some embodiments, the system may allow a user to choose two buffers from among a plurality of buffers for comparison.

Method and system for annotation and connection of electronic documents
11514234 · 2022-11-29 · ·

A method and system for annotating and linking electronic documents is described herein. Separate annotation layers or connectors are used to store each annotation or connection associated with a document in order to improve the efficiency and robustness of collaborative annotation. When a user creates an annotation for a document, a new annotation layer is generated, containing information describing the annotation. The annotation layer is separate from the annotated document. The annotation layer may be transmitted to another user without transmission of the document, thereby reducing network traffic and avoiding metadata contamination within the document itself. This facilitates real-time collaborative annotation of electronic documents by multiple users. This also facilitates robust connections between documents or other data sources, which contain information regarding both the source and target documents.

Spreadsheet and method for updating same

A computer software program for improving electronic spreadsheets to manage and control scenarios. The program provides methods for the user to record specific changes made to selected value of cells in the spreadsheet. Each recorded item can be dragged and re-ordered via a graphical user interface (GUI) to build up a scenario script. The script can be executed whereby the spreadsheet is updated with the recorded items. The method allows complex scenarios to be played back in step by incremental step, modified, re-ordered, corrected, and re-played while generating user-defined output reports & charts detailing each step change. The method provides a detailed information trail of all value changes made to the spreadsheet suitable for an independent third-party review. Different scenario components can be recorded in parallel by multiple users and then merged to produce a complete solution. The method is scalable and suitable for scenarios requiring thousands of cell value updates (subject to available computer memory, operating system limitations, and calculation time constraints).

Automated Social Agent Interaction Quality Monitoring and Improvement

A system for monitoring and improving social agent interaction quality includes a computing platform having processing hardware and a system memory storing a software code. The processing hardware is configured to execute the software code to receive, from a social agent, interaction data describing an interaction of the social agent with a user, and to perform an assessment of the interaction, using the interaction data, as one of successful or including a flaw. When the assessment indicates that the interaction includes the flaw, the processing hardware is further configured to execute the software code to identify an interaction strategy for correcting the flaw, and to deliver, to the social agent, one or both of the assessment and the interaction strategy to correct the flaw in the interaction.

Techniques for document creation based on image sections

In an embodiment, an image reception system is communicatively coupled to an image analysis system and is configured to receive a digital image and analyze the pixels of the digital image to determine one or more regions in the digital image. For each region in the one or more regions in the digital image, the image analysis system recognizes the content in the region. A document creation system communicatively coupled to the image analysis system is configured to create a digital document based on the recognized content for the one or more regions. In some embodiments, the image analysis system is further configured to analyze the digital image to detect one or more of the following: region markers, tables, headers.

Intelligent conversational gateway

A method comprises receiving at least one natural language input, and determining an intent of the at least one natural language input. In the method, a virtual assistant of a plurality of virtual assistants is recommended to respond to the at least one natural language input based at least in part on the determined intent, and the at least one natural language input is transmitted to the recommended virtual assistant. The determining and recommending are performed using one or more machine learning models, and the plurality of virtual assistants respectively correspond to a plurality of different functions of an enterprise.