In this paper, we introduce Latent Semantic Modeling (LSM), a sample-efficient alternative for pre-training encoder-based language models that does not require the use of a special mask symbol. Thi...
<p><strong>Tác giả:</strong> Gábor Berend</p>
<p>In this paper, we introduce Latent Semantic Modeling (LSM), a sample-efficient alternative for pre-training encoder-based language models that does not require the use of a special mask symbol. This is beneficial, as it allows us to perform pre-training on naturally occurring sentences (as opposed to such ones that contain an unnatural mask symbol, which symbol is otherwise not included during fine-tuning). The main idea behind LSM is that instead of requiring the language model to return the...</p>
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