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MACE is presented, a Multi-Agent Candidate Event acquisition method that refines event structure before linking and improves event linking through better candidate event acquisition without modifying the event linking model.
This work introduces ConfQA, a fine-tuning strategy that reduces hallucination rates from 20-40% to below 5% across multiple factuality benchmarks, and proposes ConfRAG, a triggering strategy that invokes RAG only when the model responses with unsure.
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