LGSE: Lexically Grounded Subword Embedding Initialization for Low-Resource Language Adaptation
Adapting pretrained language models to low-resource, morphologically rich languages remains a significant challenge. Existing vocabulary expansion methods typically rely on arbitrarily segmented subword units, resulting in fragmented lexical representations and loss of critical morphological information. To address this limitation, we propose the Lexically Grounded Subword Embedding Initialization (LGSE) framework, which introduces morphologically informed segmentation for initializing embeddings of novel tokens. Instead of using random vectors or arbitrary subwords, LGSE decomposes words into their constituent morphemes and constructs semantically coherent embeddings by averaging pretrai...
| Authors | Hailay Teklehaymanot, Dren Fazlija, Wolfgang Nejdl |
|---|---|
| Primary category | cs.CL |
| Published | 23 March 2026 |
| Last updated at source | 23 March 2026 |
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