TACENR introduces a contrastive-learning method that identifies the most influential attribute, proximity, and structural features in node representations in a task-agnostic manner.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
PriHA is a tri-stage RAG framework with query optimization and dual retrieval that outperforms baselines on accuracy and clarity for Hong Kong primary healthcare queries.
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TACENR: Task-Agnostic Contrastive Explanations for Node Representations
TACENR introduces a contrastive-learning method that identifies the most influential attribute, proximity, and structural features in node representations in a task-agnostic manner.
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PriHA: A RAG-Enhanced LLM Framework for Primary Healthcare Assistant in Hong Kong
PriHA is a tri-stage RAG framework with query optimization and dual retrieval that outperforms baselines on accuracy and clarity for Hong Kong primary healthcare queries.