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LCoT-GV: Graph Attention Networks for Verifying Long Reasoning Chains in Large Language Models
Large Reasoning Models produce Long Chains-of-Thought (LCoTs) which involve breaking down the problem into smaller reasoning steps before reaching the conclusion. However, these steps often contain contradictions, unsupported inferences, or irrelevant steps, even when the final answer is correct. We propose Long Chain-of-Thought Graph Verifier (LCoT-GV), a graph-based framework that represents LCoTs as reasoning graphs. Each node in the graph represents a reasoning step and the edges encode semantic and logical relations. A Graph Attention Network is then trained to predict chain-of-thought co
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T12:21:22.000Z
First collected: 2026-09-21T07:01:58.596Z. This is not the publication date.