ART: Adaptive Reasoning Trees for Explainable Claim Verification (2026.findings-eacl)
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Sahil Wadhwa, Himanshu Kumar, Guanqun Yang, Abbaas Alif Mohamed Nishar, Pranab Mohanty, Swapnil Shinde, Yue Wu
| Challenge: | Large Language Models (LLMs) are powerful candidates for complex decision-making, leveraging vast encoded knowledge and remarkable zero-shot abilities. |
| Approach: | They propose a hierarchical method for claim verification that uses a root claim and a pairwise tournament of its children to determine an argument's strength. |
| Outcome: | The proposed method outperforms baseline methods on multiple datasets and shows that it is more reliable and clearer than existing methods. |
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