AI Research
POSPAN: Position-Constrained Span Masking for Language Model Pre-training
Advancing natural language understanding through position-aware span masking strategies.
Span-level masked language modeling (MLM) has shown to be advantageous to pre-trained language models over the original single-token MLM, as entities/phrases and their dependencies are critical to language understanding. Previous works only consider span length with some discrete...
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ArXiv CS.LG
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ArXiv CS.LG
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POSPAN introduces position-constrained span masking to better capture the structural dependencies between entities and phrases during pre-training. By moving beyond simple length-based masking, this technique enhances a model's ability to grasp complex linguistic nuances and contextual relationships.
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