mlsanityData to 7 Oct 2026

ART: Adaptive Reasoning Trees for Explainable Claim Verification

arXiv 2601.05455 ↗First posted 9 Jan 2026cs.AI cs.LGcited by 0

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

Large Language Models (LLMs) are powerful candidates for complex decision-making, leveraging vast encoded knowledge and remarkable zero-shot abilities. However, their adoption in high-stakes environments is hindered by their opacity; their outputs lack faithful explanations and cannot be effectively contested to correct errors, undermining trustworthiness. In this paper, we propose ART (Adaptive Reasoning Trees), a hierarchical method for claim verification. The process begins with a root claim, which branches into supporting and attacking child arguments. An argument's strength is determined bottom-up via a pairwise tournament of its children, adjudicated by a judge LLM, allowing a final, transparent and contestable verdict to be systematically derived which is missing in methods like Chain-of-Thought (CoT). We empirically validate ART on multiple datasets, analyzing different argument generators and comparison strategies. Our findings show that ART's structured reasoning outperforms strong baselines, establishing a new benchmark for explainable claim verification which is more reliable and ensures clarity in the overall decision making step.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 26 of its 48 references that are in the map. First posted on arXiv 9 Jan 2026.

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26 of 48 references.

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Same direction, newest first

  1. 2025Step-by-Step Fact Verification System for Medical Claims with Explainable Reasoning20 Feb

Other references · 25

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  5. 2024Clifford Group Equivariant Simplicial Message Passing Networkscited by 22
  6. 2025Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignmentcited by 14
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  11. 2024LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Viewscited by 4
  12. 2024Northeastern Uni at Multilingual Counterspeech Generation: Enhancing Counter Speech Generation with LLM Alignment through Direct Preference Optimizationcited by 4
  13. 2024Mathematical modelling of flow and adsorption in a gas chromatographcited by 2

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