Vision models show a phase transition where accuracy on a zero syntactic-distance global-semantics task collapses to chance beyond a critical scale and does not recover with larger models or data.
arXiv preprint arXiv:2601.19393 , year=
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Claims a finite analogue of Gödel incompleteness in K-SAT by building locally indistinguishable SAT/UNSAT pairs in log-width ensemble, implying sublinear deductive systems require wide clauses and exponential proof sizes, reframing SETH as Gödel projection.
Solution independence distinguishes hypergraph dominating set from vertex cover, enabling irreducible self-referential instances that force algorithms to examine nearly the full input.
citing papers explorer
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Can Machines Really See Objects in Images? A Study Based on Syntactic Distance and Visual Self-Referential Instances
Vision models show a phase transition where accuracy on a zero syntactic-distance global-semantics task collapses to chance beyond a critical scale and does not recover with larger models or data.
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Self-Referential $K$-SAT and the Finite Analogue of G\"odel's Incompleteness Theorem
Claims a finite analogue of Gödel incompleteness in K-SAT by building locally indistinguishable SAT/UNSAT pairs in log-width ensemble, implying sublinear deductive systems require wide clauses and exponential proof sizes, reframing SETH as Gödel projection.
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Solution independence and self-referential instances
Solution independence distinguishes hypergraph dominating set from vertex cover, enabling irreducible self-referential instances that force algorithms to examine nearly the full input.