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smt-solvers

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alizangeneh / LLM-Safety-Verification

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A robust framework for formal verification of multi-agent systems powered by LLMs, ensuring safe and reliable decision-making. Integrates machine learning with formal methods to validate agent behaviors, safety constraints, and real-world simulations in critical domains like autonomous driving and robotics.

machine-learning symbolic-execution temporal-logic autonomous-vehicles formal-verification bounded-model-checking collision-avoidance multi-agent-systems ai-safety data-integrity ai-systems verification-tools safety-verification llm smt-solvers
  • Updated Feb 20, 2026
  • Python

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