CamemBERT
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Related Articles from SNS
Geometry of Semantic Space: Comparative Study of Discrete and Continuous Models
Announce Type: new Abstract: This work examines the semantic geometry underlying NLP models. We compare supervised vector embeddings, such as CamemBERT, with lexical co-occurrence graphs that encode semantic relations more directly. While transformer-based embeddings achieve strong performance, their induced geometries often display unsatisfactory distributions.