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Found 2 papers, 2 papers with code
Character-based Thai Word Segmentation with Multiple Attentions
These models estimate word boundaries from a character sequence.
Ranked #2 on
Thai Word Segmentation
on BEST-2010
LATTE: Lattice ATTentive Encoding for Character-based Word Segmentation
Our model employs the lattice structure to handle segmentation alternatives and utilizes graph neural networks along with an attention mechanism to attentively extract multi-granularity representation from the lattice for complementing character representations.
Ranked #1 on
Chinese Word Segmentation
on CTB6
(using extra training data)
