Mage shows compile-pass rate is anti-correlated with functional correctness in LLM game scene generation; direct NL-to-C# yields 43% runtime but F1~0.12 structure, while IR conditioning recovers structure (F1 up to 1.0) but halves runtime, with granularity levels statistically equivalent.
Neural computation , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
years
2026 2representative citing papers
Adversarial compromise of tool outputs misleads agentic AI via breadth and depth attacks, revealing that epistemic and navigational robustness are distinct and often trade off against each other.
citing papers explorer
-
Mage: Multi-Axis Evaluation of LLM-Generated Executable Game Scenes Beyond Compile-Pass Rate
Mage shows compile-pass rate is anti-correlated with functional correctness in LLM game scene generation; direct NL-to-C# yields 43% runtime but F1~0.12 structure, while IR conditioning recovers structure (F1 up to 1.0) but halves runtime, with granularity levels statistically equivalent.
-
How Adversarial Environments Mislead Agentic AI?
Adversarial compromise of tool outputs misleads agentic AI via breadth and depth attacks, revealing that epistemic and navigational robustness are distinct and often trade off against each other.