Can You Check That? The Checkability Boundary for Local LLM Network Automation

arXiv:2609.31540 · cs.NI, cs.AI · Submitted 2026-09-25 · Read on arXiv

cs.NI, cs.AI

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

• Accuracy — 26× in this paper · explained in 1 episode
• Aggregation — 9× in this paper · explained in 1 episode
• Grounding — 6× in this paper · explained in 3 episodes
• Verification — 6× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Verifier — 3× in this paper · explained in 2 episodes
• Hallucination — 2× in this paper · explained in 3 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• SMT solver — 1× in this paper · explained in 2 episodes

Sources

• CodeT: Code Generation with Generated Tests
• FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance
• Verifying LLM-Generated Code in the Context of Software Verification with Ada/SPARK
• RouteLLM: Learning to Route LLMs with Preference Data
• OnionEval: An Unified Evaluation of Fact-conflicting Hallucination for Small-Large Language Models
• Self-Consistency Improves Chain of Thought Reasoning in Language Models

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