Meta Answering for Machine Reading

Borschinger Benjamin
Borschinger Benjamin
Buck Christian
Buck Christian
Bulian Jannis
Bulian Jannis
Huebscher Michelle Chen
Huebscher Michelle Chen
Gajewski Wojciech
Gajewski Wojciech
Nogueira Rodrigo
Nogueira Rodrigo
Saralegu Lierni Sestorain
Saralegu Lierni Sestorain
Cited by: 1|Views3

Abstract:

We investigate a framework for machine reading, inspired by real world information-seeking problems, where a meta question answering system interacts with a black box environment. The environment encapsulates a competitive machine reader based on BERT, providing candidate answers to questions, and possibly some context. To validate the ...More

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