Papers with Sememe-Driven Language Model

1 papers
Language Modeling with Sparse Product of Sememe Experts (D18-1)

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Challenge: Existing language modeling methods rely on large-scale text data to learn the sequential patterns of words.
Approach: They propose to use sememes to represent the implicit semantics behind words for language modeling . they propose to employ sememe-driven language models to fine-grained semem-level semantics .
Outcome: Experiments on language modeling and the downstream application of headline generation show the effectiveness of SDLM.

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