公开(公告)号：US20220092453A1

公开(公告)日：2022-03-24

申请号：US17484881

申请日：2021-09-24

申请人： Thomson Reuters Enterprise Centre GmbH

发明人： Nadja Herger ,  Nina Stamenova Hristozova ,  Milda Norkute ,  Leszek Michalak ,  Stavroula Skylaki ,  Daniele Giofré ,  Andrew Timothy Mulder

IPC分类号： G06N5/04 ,  G06F16/23

摘要： Methods and systems for providing mechanisms for presenting artificial intelligence (AI) explainability metrics associated with model-based results are provided. In embodiments, a model is applied to a source document to generate a summary. An attention score is determined for each token of a plurality of tokens of the source document. The attention score for a token indicates a level of relevance of the token to the model-based summary. The tokens are aligned to at least one word of a plurality of words included in the source document, and the attention scores of the tokens aligned to the each word are combined to generate an overall attention score for each word of the source document. At least one word of the source document is displayed with an indication of the overall attention score associated with the at least one word.