Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method, computer system, and a computer program product for software anomaly detection is provided. The present invention may include, receiving a target source code including a sequence of tokens. The present invention may also include, determining a probability of a candidate token in the sequence of tokens based on a context of other tokens in the sequence of tokens. The present invention may further include, in response to the determined probability of the candidate token satisfying a low probability threshold, detecting a low probability region in the received target source code, wherein the detected low probability region is associated with the candidate token satisfying the low probability threshold.

Abstract: 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.

Abstract: 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.