Converts impossibility theorems into architecture-dependent accuracy ceilings and design rules for transformers and other AI subfields, with the Deterministic Horizon measured at 19-31 across twelve models.
On the Fundamental Impossibility of Hallucination Control in Large Language Models
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
representative citing papers
AI security and alignment cannot achieve full robustness because any sufficiently powerful AI inherits incompleteness-style limitations from formal systems.
citing papers explorer
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The Deterministic Horizon: Impossibility Results as Design Specifications for Trustworthy AI Systems
Converts impossibility theorems into architecture-dependent accuracy ceilings and design rules for transformers and other AI subfields, with the Deterministic Horizon measured at 19-31 across twelve models.
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Robust AI Security and Alignment: A Sisyphean Endeavor?
AI security and alignment cannot achieve full robustness because any sufficiently powerful AI inherits incompleteness-style limitations from formal systems.
- UnWeaving the knots of GraphRAG -- turns out VectorRAG is almost enough