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Word Embeddings Revisited: LLMs vs. Classical Models
LLMs tend to cluster semantically related words more tightly than classical models, showing higher accuracy on the Bigger Analogy Test Set.
Word Embeddings Revisited: Investigating LLMs vs. Classical Models
LLMs tend to cluster semantically related words more tightly than classical models, showing higher accuracy on analogy tasks.
Analyzing Word Embeddings: LLMs vs. Classical Models
The author compares Large Language Models (LLMs) with classical models like Sentence-BERT and Universal Sentence Encoder to determine if the performance improvement is due to scale or fundamentally different embeddings. The approach involves analyzing semantic clustering and accuracy on analogy tasks.
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