Logical reasoning remains a major challenge for large language models (LLMs), particularly on structured problems that require precise constraint tracking, consistency preservation, and multi-step deduction. This challenge is especially acute for small-scale LLMs, which are more prone to producing inconsistent, redunda...
Muhammad Asif Ali, Wen-Qing Wang, Huan Wang et al.· 0 citations
S PRING uses SMT solver as a training-time verifier of intermediate reasoning steps to provide process-level supervision and introduces the notion of a novel reasoning step, namely, a step that is logically valid, consistent with the evolving reasoning state, and not already implied by previously accepted non-contradic...
Muhammad Asif Ali, Wen-Qing Wang, Huan Wang et al.· 0 citations
VeriSimpl is introduced, a solver LLM framework for robust natural-language-to-optimization formalization, based on the idea of simplification-based verification, where the optimization solver is leveraged to generate simplified diagnostic queries about a candidate formulation to allow the LLM to tractably reason about...
S. Rahman, Seckhen Ariel Andrade Cuellar, Ghani Raissov et al.· arXiv.org· 2 citations
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