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Evidence weighting in Homo-RAG boosts retrieval effectiveness, achieving near-perfect relevance scores while enhancing the quality of gene function predictions for non-model organisms.
Achieve 2-15% better text classification accuracy by explicitly fusing grammatical features with frozen contextual embeddings, offering a lightweight alternative to computationally intensive transformer models.
