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An Automated Question-Answering Framework Based on Evolution Algorithm. (arXiv:2201.10797v1 [cs.CL])
Web: http://arxiv.org/abs/2201.10797
Jan. 27, 2022, 2:10 a.m. | Sinan Tan, Hui Xue, Qiyu Ren, Huaping Liu, Jing Bai
cs.LG updates on arXiv.org arxiv.org
Building a deep learning model for a Question-Answering (QA) task requires a
lot of human effort, it may need several months to carefully tune various model
architectures and find a best one. It's even harder to find different excellent
models for multiple datasets. Recent works show that the best model structure
is related to the dataset used, and one single model cannot adapt to all tasks.
In this paper, we propose an automated Question-Answering framework, which
could automatically adjust network …
More from arxiv.org / cs.LG updates on arXiv.org
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