{"slug": "toe-a-hierarchical-and-explainable-claim-verification-framework-with-dynamic-and", "title": "ToE: A Hierarchical and Explainable Claim Verification Framework with Dynamic Multi-source Evidence Retrieval and Aggregation", "summary": "Researchers propose Tree of Evidence (ToE), a hierarchical claim verification framework that uses reinforcement learning-driven multi-source retrieval and argument tree aggregation to combat fake news and AI-generated misinformation. ToE achieves 4-24 percentage point improvements over baselines, especially against adversarially poisoned inputs, with a formal error bound guaranteeing near-optimal policy convergence.", "body_md": "arXiv:2606.27736v1 Announce Type: new\nAbstract: The rapid spread of fake news poses increasing threats to information ecosystems, especially as AI-generated misinformation under Generative Engine Optimization (GEO) poisoning allows adversarially crafted content to be systematically surfaced by retrieval systems, contaminating LLM reasoning. In this paper, we propose Tree of Evidence (ToE), a hierarchical evidence reasoning framework for automated fact-checking that models each claim as a dynamically expanding argument tree. ToE integrates a reinforcement learning-driven multi-source retrieval agent, an evidence evaluation agent, and an argument tree aggregation algorithm to iteratively decompose, retrieve, and verify claims through an explainable evidence chain. We further provide a theoretical analysis of the retrieval process, deriving a formal error bound that guarantees the learned policy converges to a neighborhood of the information-theoretically optimal policy. Experiments across multiple datasets and backbone LLMs demonstrate that ToE achieves improvements ranging from 4 to 24 percentage points over competitive baselines, with particularly pronounced gains on adversarially poisoned inputs.", "url": "https://wpnews.pro/news/toe-a-hierarchical-and-explainable-claim-verification-framework-with-dynamic-and", "canonical_source": "https://arxiv.org/abs/2606.27736", "published_at": "2026-06-29 04:00:00+00:00", "updated_at": "2026-06-29 04:11:01.601016+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-safety", "ai-research", "large-language-models", "natural-language-processing"], "entities": ["Tree of Evidence", "Generative Engine Optimization", "arXiv"], "alternates": {"html": "https://wpnews.pro/news/toe-a-hierarchical-and-explainable-claim-verification-framework-with-dynamic-and", "markdown": "https://wpnews.pro/news/toe-a-hierarchical-and-explainable-claim-verification-framework-with-dynamic-and.md", "text": "https://wpnews.pro/news/toe-a-hierarchical-and-explainable-claim-verification-framework-with-dynamic-and.txt", "jsonld": "https://wpnews.pro/news/toe-a-hierarchical-and-explainable-claim-verification-framework-with-dynamic-and.jsonld"}}