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We survey and compare different approaches that have been suggested in the past to solve the problem of predicting the future citation count of a scientific article after a given time interval of its publication. Further, we present a novel sequence-to-sequence learning model that outperforms current state-of-art.

License: MIT License

Python 98.83% Shell 1.17%

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