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In this paper, we present a new method of using statistical models to estimate readability [1]. Language Model is used to capture the content information. It is combined with linguistic feature model by a linear form. Experiments show that this new method has a better performance than the widely used Flesch-Kincaid readability formula.
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Stored only when both papers are in the corpus — 205 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.