Optimizing Decomposition for Optimal Claim Verification

• URL: http://arxiv.org/abs/2503.15354v2
• Date: Sun, 25 May 2025 22:54:47 GMT
• Title: Optimizing Decomposition for Optimal Claim Verification
• Authors: Yining Lu, Noah Ziems, Hy Dang, Meng Jiang,
• Abstract summary: We find that existing decomposition policies, typically hand-crafted demonstrations, do not align well with downstream verifiers in terms of atomicity.<n>We propose dynamic decomposition, a reinforcement learning framework that leverages verifier feedback to learn a policy for dynamically decomposing claims to verifier-preferred atomicity.<n> Experimental results show that dynamic decomposition outperforms existing decomposition policies, improving verification confidence by 0.07 and accuracy by 0.12 on average across varying verifiers, datasets, and atomcities of input claims.
• Score: 15.68967195914405
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Current research on the \textit{Decompose-Then-Verify} paradigm for evaluating the factuality of long-form text typically treats decomposition and verification in isolation, overlooking their interactions and potential misalignment. We find that existing decomposition policies, typically hand-crafted demonstrations, do not align well with downstream verifiers in terms of atomicity -- a novel metric quantifying information density -- leading to suboptimal verification results. We formulate finding the optimal decomposition policy for optimal verification as a bilevel optimization problem. To approximate a solution for this strongly NP-hard problem, we propose dynamic decomposition, a reinforcement learning framework that leverages verifier feedback to learn a policy for dynamically decomposing claims to verifier-preferred atomicity. Experimental results show that dynamic decomposition outperforms existing decomposition policies, improving verification confidence by 0.07 and accuracy by 0.12 (on a 0-1 scale) on average across varying verifiers, datasets, and atomcities of input claims.

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