ORSMT: Unleashing the Potential of Satisfiability Modulo Theories for Semantic Verification and Repair in LLM-Based Optimization
math.OC, cs.AI, cs.SE
Submitted: 2026-10-21
Updated: 2026-10-21
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Related papers
- Lions and Muons: Optimization via Stochastic Frank-Wolfe under Heavy-Tailed Noise
- Adam-HNAG: A Convergent Reformulation of Adam with Accelerated Rate
- Incremental Learning in Mirror Flows
- Beyond Aggregate Drift: Optimal Client-Specific Windows in Federated Learning
- Lower Bounds for Randomized Linear-Oracle Optimization over Strongly Convex Sets
- Second-Order Optimization with Asynchronous Curvature