NUS proposes Jeva, a decision-native architecture with near-perfect null detection at thousands of candidates
NationalUniversityofSingapore · hf · 2026-10-14
A National University of Singapore paper introduces Jeva, a decision-native architecture for low-latency system-one decisions, arguing current text-serialized answer prediction neglects four structural requirements: null-awareness, permutation invariance, option scalability, and cacheability.
- A shared encoder independently represents the request and each option; a compact decision stack refines request state against immutable option memory.
- Symmetric aggregation gives permutation-equivariant probabilities; shared scoring handles variable-size candidate sets.
- Evaluations show strong typed-decision performance, near-perfect null detection, zero decision flips under permutations, scaling to thousands of candidates, and reduced latency via cross-request reuse.
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