SMART: State-based Multi Agent Reasoning Traces for Verification-oriented Problem-Solving

Authors: Sai Vallurupalli , Francis Ferraro

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Abstract: Complex problems with limited context, such as claims, require a means to obtain additional knowledge necessary for solution reasoning. We propose a multi-agent framework, SMART, to obtain knowledge through capturing the implicit state of participating entities in a problem context. SMART curates the state knowledge as diverse, complementary and solution-salient premises using a variety of LLMs and a structured role-based prompt strategy. Using knowledge from these real-world verified curated premises, SMART's knowledge guided solution reasoning improves validation performance up to 20% on complex scientific claims spanning 3 datasets. We show that grounding premises in real-world knowledge is necessary and improves performance up to 5%.

Subjects:

Artificial Intelligence (cs.AI) ; Computation and Language (cs.CL)

Cite as:

arXiv:2611.08196 [cs.AI]

(or

arXiv:2611.08196v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2611.08196

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arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Sai Vallurupalli [ view email ]

[v1]

Thu, 5 Nov 2026 15:51:39 UTC (1,441 KB)

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