SOURCE-LINKED INTELLIGENCE
DARE: Dialectical Agentic Reasoning for Structured Knowledge Fact Checking
Structured knowledge fact checking aims to determine the truthfulness of natural language claims by reasoning over structured evidence. Recent program-generation approaches leverage large language models (LLMs) to generate executable graph reasoning programs, achieving strong performance on structured knowledge fact checking benchmarks. However, these methods remain limited by invalid relation generation, single-path reasoning that lacks self-correction, and biased evidence assessment that tends to overestimate supporting signals. We propose Dialectical Agentic Reasoning (DARE), a multi-agent
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-12T08:41:52.000Z
First collected: 2026-09-20T16:41:15.630Z. This is not the publication date.