Papers by Peiqiang Qiu

1 papers
ACSE: An Ancient Character Semantic-Aware Embedding for Large Language Models (2026.findings-acl)

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Challenge: Existing studies on pre-Qin documents are insufficient to understand ancient characters . ancient characters have a low level of digitization and training corpora are extremely scarce .
Approach: They propose a semantic-aware embedding for ancient Chinese characters that integrates glyphs and lexicality into modern Chinese semantic space.
Outcome: The proposed model integrates glyph and lexicality of ancient characters and maps them to the modern Chinese semantic space.

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