open-standards/wai/extensions/determinism-tiers.md

WAI Extension: Determinism Tiers for Neural Decode

Status: Draft. Names the spectrum of reproducibility guarantees a neural capability can make, so a manifest can declare which one it satisfies and a verifier knows what it may check. Positions WAI's byte-exact reconstruction (decode-equivalence) as the strongest tier above the entropy-stage guarantee the base learned-codec field provides. No new wire format; a vocabulary + conformance framing over §7. Keywords MUST, MUST NOT, SHOULD, MAY are RFC 2119/8174.

1. Why tiers

Neural decode reproducibility is not binary. A float neural decode is not reproducible at all — round-off diverges across hardware, and one diverging bit corrupts a learned entropy decode. In response the field has converged on making the entropy stage reproducible while leaving reconstruction to pixels implementation-defined. Two facts make this concrete:

• The base standard. JPEG AI (ISO/IEC 6048) defines its normative bit-exact conformance point at the output of the entropy decoder, not at reconstruction to pixels; its entropy pipeline is integer so that stage replicates across devices, while post-entropy processes MAY diverge. One codestream may legally reconstruct through up to three synthesis transforms.
• The learned-codec field. The mainstream cross-platform fix is explicit parameter transmission — carrying the entropy/scale parameters in the codestream so the entropy decode is consistent across devices without requiring bit-exact arithmetic. Same target: a reproducible entropy stage, a reconstruction that may vary.

WAI supports that guarantee and a stronger one. Naming both lets a capability be honest about which it makes, and lets a receipt or a provenance binding (§reconstruction-binding) demand the tier it needs.

2. The tiers

entropy-consistency

The entropy decode reproduces byte-for-byte across devices — the decoded symbols / quantized latent have a portable hash — but the reconstruction to the final medium (pixels, samples) MAY differ between conforming sinks. A sink achieves this either by integer entropy arithmetic (deriving the coding parameters with fixed-point ops, as WAI's integer decoders and JPEG AI's entropy pipeline do) or by explicit parameter transmission (the codestream carries the parameters, so no bit-exact derivation is required).

• Conformance criterion: entropy-equivalence — a verifier decodes the entropy stage and compares the symbols / quantized latent, NOT the pixels.
• This is the guarantee the base learned-codec standard and the mainstream cross-platform techniques provide. It is the floor for a sound neural replicate under §7: enough that the decode does not catastrophically desync, not enough to hash the rendered result.

decode-equivalence

The whole decode to the final medium reproduces byte-for-byte across devices — the reconstructed pixels (or samples, or attributes) have a portable hash. The sink pins one reconstruction and runs it in integer / fixed-order arithmetic end to end, entropy and synthesis. Where the base codec admits several conformant reconstructions, this tier fixes one.

• Conformance criterion: the medium's *-equivalence (e.g. decode-equivalence for wai.image.jpegai, sample-equivalence for wai.audio.int_codec, splat-equivalence for wai.splat.int_codec).
• This is WAI's contribution above the field's baseline: it is a determinism guarantee beyond what the base standard requires, and it is the precondition for a hard provenance binding over the rendered content — a decoded-pixel hash is only portable when the reconstruction is pinned.

A capability satisfying decode-equivalence satisfies entropy-consistency by construction; the reverse does not hold.

What a tier covers

A tier is a property of the whole path from codestream to the medium that is hashed, bound, or presented — not of the decode stage in isolation. A sink that decodes conformantly and then alters the result has not satisfied the tier, however faithful the decode itself was.

This is not hypothetical. Two mechanisms in force today change the medium after a conformant decode, and both arrive through the same pipe as the codestream:

• Post-decode neural filters. ITU-T H.274 (V4, 01/2026) nnpfc / nnpfa SEI messages activate a neural post-filter after decoding, changing output pixels. The filter may be named by URI or carried in-band.
• Operation-reduction hints. ISO/IEC 23001-11 (green metadata) carries decoding-operation-reduction metadata whose express purpose is to let a decoder spend fewer joules by doing less work — deliberate degradation, signalled in-band and invisible to a conformance check that stops at the decoder.

The rules:

• A sink claiming a tier MUST evaluate it over the medium it emits. If it applies post-decode processing that alters that medium, it MUST either not apply the processing, or MUST NOT claim the tier for the emitted result.
• An object that honours a decoding-operation-reduction hint MUST NOT claim decode-equivalence, and a receipt over its output MUST NOT carry a reproducible decoded-medium hash. Spending fewer joules by computing less is a fidelity choice; a receipt that reports the joules while concealing the degradation states a cost without its consideration.
• A capability's registration SHOULD state whether its payload can carry post-decode processing directives at all. A capability whose payload cannot is unaffected by this section, and saying so is cheaper than leaving it open.

The general rule, which is why this section exists: a determinism claim covers what the sink emits. A hash over a decode that something later modified describes an artifact nobody saw — the hash verifies, and it attests the wrong thing.

3. Declaring and using a tier

• A capability's registration (§5) states its tier via its *-equivalence criterion; the WAI capabilities that decode a learned image/audio/3D latent to bytes (wai.image.jpegai, wai.neural.int_*, wai.audio.int_codec, wai.splat.int_codec) are decode-equivalence. A capability MAY instead declare entropy-consistency when it only guarantees the entropy stage.
• replicate-soundness (§7). An envelope with intent = replicate MUST pin a prior that meets at least entropy-consistency; a float neural decode meets neither tier and MUST NOT claim replicate. A receipt that carries a reproducible decoded-medium hash MUST come from a decode-equivalence capability.
• Post-decode processing. A tier claim is void if the sink alters the medium after decode (§2, What a tier covers). This applies to the emitted result, not to the decoder's internal conformance.
• Provenance. The reproducible-reconstruction binding — a C2PA / JPEG-Trust hard binding over decoded pixels — requires decode-equivalence; over an entropy-consistency capability only the entropy-stage output is bindable, not the rendered result.

4. Framing

Both tiers here are reproducibility guarantees: a sink can check them from the bytes it received. A separate axis exists for media whose correctness is a downstream model's behaviour rather than a byte comparison — see task-fidelity, which is a sibling rather than a third tier precisely because such a claim is not sink-checkable from the bytes.

WAI spans the spectrum rather than competing on one point of it. The entropy-consistency tier is the base learned-codec floor — the guarantee the field and the underlying standards already make — and WAI supports it directly. decode-equivalence is the tier WAI adds on top: pinning one full reconstruction so the rendered result, not only the entropy stream, is reproducible and hashable. Both are stated as capabilities of the standard, not as comparisons.