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Multilingual Language Processing From Bytes

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Figure

Figure 1: A diagram showing the way the Byte-to-Span (BTS) model converts an input text segment to a sequence of spanannotations
Table 1: Part-of-speech tagging accuracy for two CRF base-lines and 2 versions of BTS
Table 2: A comparison of NER systems. The results are F1scores, where a correct span annotation exactly matches a goldspan annotation (start, length, and entity type must all be cor-rect)
Figure 2: A tSNE plot of the BTS model’s memory state just before the softmax layer produces one of the NER labels.

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