Unverified50% confidenceFactExact time
QuanLing's methodology combines three indicators: sentence embedding distance, tokenization fragmentation rate, and masked language model mutual intelligibility.
1
Sources
50%
Confidence
Long-term
Relevance
10/8/2026
First Seen
Sources
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Related Claims
UnverifiedSynonym normalization can be achieved by using sentence embedding models such as Sentence-BERT to map words into dense vectors, and then computing semantic proximity via cosine similarity.75% similarUnverifiedSentence-BERT通过孪生网络结构将句子映射为固定维度的稠密向量，专为句子级语义相似度优化70% similarUnverifiedSemantic chunking uses embedding models to assess semantic similarity between adjacent sentences and splits at semantic breaks, but still cannot guarantee logical coherence across paragraphs.69% similarVerifiedSemantically similar texts are also close in distance within vector space, which is the mathematical foundation of vector retrieval.69% similar
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