146 citations · 155 across the 7 of their papers we have counts for
Showing 2019 · cs.CLShow all
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cs.CL2019
Tabula nearly rasa: Probing the Linguistic Knowledge of Character-Level Neural Language Models Trained on Unsegmented Text
Michael Hahn, Marco Baroni
Recurrent neural networks (RNNs) have reached striking performance in many natural language processing tasks. This has renewed interest in whether these generic sequence processing…
cs.CL2019★ 146 cited
Theoretical Limitations of Self-Attention in Neural Sequence Models
Michael Hahn
Transformers are emerging as the new workhorse of NLP, showing great success across tasks. Unlike LSTMs, transformers process input sequences entirely through self-attention. Previ…
cs.CL2019★ 1 cited
Character-based Surprisal as a Model of Reading Difficulty in the Presence of Error
Michael Hahn, Frank Keller, Yonatan Bisk +1
Intuitively, human readers cope easily with errors in text; typos, misspelling, word substitutions, etc. do not unduly disrupt natural reading. Previous work indicates that letter…