VERAS: Verification-Guided Adaptive Search for Reliable Operations Research

Key points

• Advances in reasoning, coding, and tool use enable LLM agents to solve operations research (OR) problems through iterative problem modeling, program construction, and verification.1
• Yet passing self-authored verification does not ensure that the solutions satisfy task constraints and meet optimization quality.1
• This gap can arise from correlated specification errors, where the generated program and its checks share omissions or misinterpretations of task requirements, alongside incomplete verification coverage and ineffective optimization strategies.1
• VERAS combines task-specific solution checkers with a separate verification agent to examine candidate solutions against the task requirements.1

Sources (1)

• [1]VERAS: Verification-Guided Adaptive Search for Reliable Operations Research
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 16, 11:50 PM

  We propose VERAS, a verification-guided adaptive search harness for reliable OR that uses verification evidence to prioritize feasibility repair, constraint-coverage review, and solution-quality improvement.

  Advances in reasoning, coding, and tool use enable LLM agents to solve operations research (OR) problems through iterative problem modeling, program construction, and verification.

Extractive summary: sentences quoted from the sources.