Finetuning text encoders on taxonomy-guided, LLM-generated negation and hedging triples substantially improves negation benchmark performance while keeping general embedding quality roughly intact.
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Learning Robust Negation Text Representations
Finetuning text encoders on taxonomy-guided, LLM-generated negation and hedging triples substantially improves negation benchmark performance while keeping general embedding quality roughly intact.