LLM agents in a solver-aware harness recover global constraints from MIP formulations, generate executable propagation-only handlers for SCIP, and solve five additional MIPLIB 2017 instances.
AutoSAT: Automatically optimize SAT solvers via large language models
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IC3-Evolve evolves IC3 heuristics via offline LLM patches that are admitted only after passing proof or witness validation, yielding standalone improved checkers evaluated on HWMCC and unseen benchmarks.
Synthetic data improves models only in information-open generation-training loops with external signals, and coarser signals like binary correctness enable better generalization by converging to the most information-efficient component.
MEP uses LLMs in a structured reasoning cycle to evolve improved heuristics for HGS on VRPs, achieving up to 2.7% better solution quality and over 45% reduced runtime.
A survey compiling roles, applications, benchmarks, challenges, and future directions for large language models in operations research.
citing papers explorer
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Agentic MIP Research: Accelerated Constraint Handler Generation
LLM agents in a solver-aware harness recover global constraints from MIP formulations, generate executable propagation-only handlers for SCIP, and solve five additional MIPLIB 2017 instances.
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IC3-Evolve: Proof-/Witness-Gated Offline LLM-Driven Heuristic Evolution for IC3 Hardware Model Checking
IC3-Evolve evolves IC3 heuristics via offline LLM patches that are admitted only after passing proof or witness validation, yielding standalone improved checkers evaluated on HWMCC and unseen benchmarks.
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An Information-Theoretic Criterion for Efficient Data Synthesis
Synthetic data improves models only in information-open generation-training loops with external signals, and coarser signals like binary correctness enable better generalization by converging to the most information-efficient component.
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PyVRP$^+$: LLM-Driven Metacognitive Heuristic Evolution for Hybrid Genetic Search in Vehicle Routing Problems
MEP uses LLMs in a structured reasoning cycle to evolve improved heuristics for HGS on VRPs, achieving up to 2.7% better solution quality and over 45% reduced runtime.
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Large Language Models for Operations Research: A Comprehensive Survey
A survey compiling roles, applications, benchmarks, challenges, and future directions for large language models in operations research.