BGM-HAN, a hierarchical attention model enhanced with byte-pair encoding, multi-head attention, and gated residuals, reports 85% accuracy on a proprietary admissions dataset, beating several baselines but with no significance testing.
In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
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BGM-HAN: A Hierarchical Attention Network for Accurate and Fair Decision Assessment on Semi-Structured Profiles
BGM-HAN, a hierarchical attention model enhanced with byte-pair encoding, multi-head attention, and gated residuals, reports 85% accuracy on a proprietary admissions dataset, beating several baselines but with no significance testing.