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Generative Verification (GenV) is introduced, which distills an offline Z3-equivalence oracle into a reference-free, continuous reference-equivalence score by repurposing the language model's native vocabulary space and theoretically proves that structural, verdict-only verification heuristics are mathematically bounded to chance-level detection on these deceptively valid traces.
StochBench is introduced, a Lean 4 benchmark of 450 graduate stochastic-processes problems at varying abstraction levels, each paired with its natural-language source that better represents domain-specific applied mathematics while remaining challenging for advanced provers.
Cross-lingual fairness gaps in language model watermarking are not just language-specific but are fundamentally tied to the structural properties of language families.
