International Business Machines Corporation

Stephanie Houde

John Thomas Richards

Steven I Ross

Fernando Carlos Martinez

Justin David Weisz

Yunfeng Zhang

Michael Muller

Qingzi Vera Liao

David John Piorkowski

Sameep Mehta

Ramya Raghavendra

Kalapriya Kannan

Kush Raj Varshney

Aleksandra Mojsilovic

Darrell Christopher Reimer

Rachel K E Bellamy

Manish Kesarwani

Matthew R Arnold

Kaoutar El Maghraoui

Michael James Hind

Kartik Talamadupula

Rachel Katherine Emma Bellamy

Vera Liao

Mayank Agarwal

Kristina Marie Brimijoin

Jason Tsay

David John Pirokowski

Rachel Katherine Emma Ballamy

Computer-implemented methods for determining and displaying correspondence between source data and target data. Aspects include receiving source tokens associated with source data and target tokens associated with target data, generating source encodings for each source token of the set of source tokens, and generating target encodings for each target token of the set of target tokens. Aspects include receiving an indication of a selected source token associated with the source data. Aspects further include determining an identified target token from the set of target tokens corresponding to the selected source token by calculating distances between the selected source token and each of the target tokens in the high-dimensional latent space using the source encodings and the target encodings. Aspects include displaying a correspondence between a portion of the source data corresponding to the selected source token and a portion of the target data associated with the identified target token.

Determining and displaying correspondences between source data and target data from a translation process

Embodiments relate to interactive editing of a machine-generated document. A computer-implemented method includes receiving, by a processor, a machine-generated document and performing a comparison of a current state of the machine-generated document to a previous state. A user edit is identified as one or more user-replaced tokens of a previous token sequence based at least in part on the comparison. A new version of the machine-generated document is generated that includes the one or more user-replaced tokens and identifies one or more related tokens to replace with a suggested replacement token sequence associated with the one or more user-replaced tokens. A suggestion list is generated for display to the user in a graphical user interface to indicate the suggested replacement token sequence to replace the one or more related tokens.

Interactive editing of a machine-generated document

In an approach for assisting a user to remain focused on a task, a processor collects a plurality of information regarding one or more digital activities of a user. A processor tokenizes the plurality of information into one or more vectorized embeddings. Responsive to determining that the user has engaged a focus mode, a processor intercepts one or more communications. A processor synthesizes, utilizing a large language model and the one or more vectorized embeddings, one or more natural language responses to the one or more communications. A processor transmits the one or more natural language responses to one or more originating users of the one or more communications. Responsive to determining that the user has ended the focus mode, a processor displays a summary of the one or more communications and the one or more natural language responses transmitted while the user was in the focus mode.

Summarization for attention management and recall

An autonomous agent operating method, system, and computer program product, including launching a first autonomous agent for a task with an initial update interval and adjusting the initial update interval for a second autonomous agent based on a second task for the second autonomous agent being similar to the task over time in relation to a trust level of a human user in a performance of the first autonomous agent.

Increasing trust formation and reduce oversight costs for autonomous agents

A computer-implemented method for counterfactual conversation simulation is disclosed. The computer-implemented method includes generating a system output based, at least in part, on a user input. The computer-implemented method further includes determining that a system output/user input pair is not satisfactory based, at least in part, on a system output/user input score being below a predetermined threshold. The computer-implemented method further includes generating, in response to determining the system output/user input pair is not satisfactory, a counterfactual simulation of the user input based, at least in part, on a target intent of the user input.

Conversational agent counterfactual simulation

Embodiments relate to interactive graphical display. A request is processed by a generative system to generate multiple hypotheses of an output in response to the request, a primary hypothesis of the multiple hypotheses having a highest confidence for the output, multiple secondary hypotheses of the multiple hypotheses having a lower confidence than the highest confidence. At least one region of divergence is determined from the primary hypothesis by the multiple secondary hypotheses, the at least one region of divergence having alternatives in the multiple secondary hypotheses, the alternatives in the multiple secondary hypotheses differing from the primary hypothesis. A graphical user interface displays the at least one region of divergence in the primary hypothesis and alternatives in the multiple secondary hypotheses for the at least one region of divergence, the alternatives and primary hypothesis for the at least one region of divergence being displayed as selectable options for a user.

Interactive graphical display of multiple overlapping hypotheses or document versions

An autonomous agent operating method, system, and computer program product, including configuring an autonomous agent for a task, launching the autonomous agent with an initial update interval, the update interval determining a frequency of the autonomous agent reporting results to a human user for review, measuring the trust level of human user in a performance of the autonomous agent, and dynamically adjusting the update interval based on this measured trust.

According to a first aspect of the present invention, a computer implemented method, a computer system and a computer program product for creating an ontological conversational agent, the method including creating an ontological specification of a domain of discourse of the ontological conversational agent, and creating a description of one or more goals of the ontological conversational agent. In an embodiment, the ontological description includes classes of entities, their associated attributes and relationships between the classes of entities. In an embodiment, the ontological description includes language-related descriptions. In an embodiment, the method, computer system and computer program product further includes creating a description of services of the ontological conversational agent. An embodiment including receiving a first utterance from a user during a conversation, identifying a first intent based on the first utterance, and recognizing a first goal of the one or more goals, based on the first intent.

Ontology-based organization of conversational agent

A method of using artificial intelligence to provide source code from an original programming language in a target programming language showing regions of low confidence. The method includes receiving, by a computing device, a code base in an original programming language. The computing device further provides the code base in the original programming language to a target programming language using an artificial intelligence tool. The computing device additionally displays the code base in the target programming language using a visualization tool in a visual interface. The computing device still further displays the regions of uncertainty to a human user in the visual interface. The regions of uncertainty provide low confidence regions of the code base in the target programming language for targeted user intervention. The regions of low confidence correlate with violations to provide displayed actionable insight regions.

Computer assisted programming with targeted visual feedback

A method for automatically generating documentation for an artificial intelligence model includes receiving, by a computing device, an artificial intelligence model. The computing device accesses a model facts policy that indicates data to be collected for artificial intelligence models. The computing device collects artificial intelligence model facts regarding the artificial intelligence model according to the model facts policy. The computing device accesses a factsheet template. The factsheet template provides a schema for an artificial intelligence model factsheet for the artificial intelligence model. The computing device populates the artificial intelligence model factsheet using the factsheet template with the artificial intelligence model facts related to the artificial intelligence model.

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Belmont, MA, United States of America

Stephanie Houde