# Typed-Reference Composition: Every Reference Image Has One Job
Author: Alex Nikulin (Александр Никулин) — https://www.alexnix.com
Original: https://www.alexnix.com/en/articles/typed-reference-composition · Published: 2026-04-20 · Updated: 2026-04-20
License and terms of use: © Alex Nikulin. Quoting and referencing are permitted only with credit to the author and a link to the original. Copying, republishing or paraphrasing without attribution is prohibited.

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> A prompt architecture for multi-input image generation: every reference carries an explicit typed role, and the prompt names inline which reference contributes which dimension. Stops silent-reference hallucination at its source.

Tags: prompt-architecture, references, composition, multi-image, image-generation

Your pipeline attaches four references to a generator: a person, a pose, a background, a piece of clothing. You write the prompt: "the subject in this pose, wearing these clothes, in this background." The model pulls clothes from the person reference **and** from the clothing reference. The pose reference also contributes a hairstyle. The background contributes a stray figure. Your prompt didn't tell the model "use reference 4 for clothing only, ignore everything else in it" — so it didn't. And you can't diagnose which reference caused which contamination because all four were silent contributors.

The fix is to give every reference an **explicit typed role** and to declare that role **inside the prompt text the generator reads** — so the model never has to guess which reference answers which question.

**Typed-reference composition** is a prompt architecture for multi-input generation where every reference image carries an explicit typed role and the prompt text declares, inline, which reference contributes which dimension. It stops silent-reference hallucination at its source.

## The shape

```
Input references
├── Image 1 → refType: "identity"       (face, body, skin tone — ignore clothes/background)
├── Image 2 → refType: "pose"           (body position — ignore appearance/clothes/location)
├── Image 3 → refType: "background"     (environment — ignore subjects)
├── Image 4 → refType: "clothing"       (garment form, fabric, colour — ignore the model wearing it)
└── Image 5 → refType: "product"        (object form, orientation, text — ignore context)

System prompt:
  IMAGE ORDER
  ─────────────
  Image 1: Identity reference
  Image 2: Pose reference (pose only — ignore person)
  Image 3: Background reference
  ...

  RULE: In every prompt, state explicitly which image contributes what.
  RULE: Do not use image numbers that don't exist in IMAGE ORDER.

Emitted prompt (for the generator):
  "... using Image 1 for identity (face/body/skin), Image 2 for pose only
   (ignoring the person depicted), Image 3 for environment (ignoring any
   subjects present), ..."
```

## The three moving parts

1. **refType** — a typed role per reference. The type names what dimensions the reference provides *and implicitly* what it does not.
2. **IMAGE ORDER** — a positional declaration shared between system prompt and emitted prompt. Gives every reference a stable, explicit identity.
3. **Inline declaration** — the LLM is instructed to name, inside every prompt, what every attached reference is doing. No silent reference usage.

All three are load-bearing. Remove any one and silent-reference hallucination returns.

## Why it works

Generative image models receiving N reference images will use all of them — that's the whole point of conditioning. The problem isn't "too many references"; it's "no guidance on which reference answers which question." A clothing reference that also happens to contain a model becomes a second identity source unless *explicitly typed* as clothing-only.

The pattern converts the implicit "use these images however seems sensible" contract into an explicit "Image 2 is pose only, ignore the person depicted" contract. The model still makes judgment calls, but within a much narrower space.

## Failure modes

- **Untyped reference attachment.** A reference without a declared role is interpreted by the model as "use however seems relevant" — which silently pulls the wrong dimension. Catch: every reference must carry a refType at ingest time.
- **Implicit typing via image position alone.** "Image 1 is always identity" breaks when some users don't attach Image 1. An explicit IMAGE ORDER with current state, per-call, is load-bearing.
- **Declaration in system prompt only, not in the emitted prompt.** If the LLM merely *knows* about the refType but doesn't write it into the output prompt, the downstream generator doesn't see it. The inline declaration is what reaches the model that matters.

## Composition

The pattern slots cleanly into bigger architectures:

- Often wrapped by a [Lock layer](https://www.alexnix.com/en/articles/lock-layer-pattern-paper) that restates the IMAGE REFERENCE MAP at the top of every final prompt — the typing reaches the generator on every call, not just at the start of a session.
- Typically produced by the architect stage of the [two-stage director / architect pattern](https://www.alexnix.com/en/articles/two-stage-architect-pattern-paper).
- Composes with [reference condensation](https://www.alexnix.com/en/articles/sequential-consistency-prompt-architecture-paper): many typed references can be merged into one coherent composite reference to reduce attention load.

A single-shot worked example of the pattern is a mixed-composition prompt builder with explicit typing for identity, pose, background, clothing, product, and technical references in one composite prompt.

## Generalises beyond image generation

Any LLM flow taking multiple typed inputs benefits:

- **Code generation from multiple file contexts** — spec file / test file / existing module, each with a declared role.
- **Document synthesis from multiple source documents** — primary / supporting / rebuttal.
- **Tool-using agents with multiple data sources** — every source declared at ingest.

The discipline — **every input has a declared role, and that role is named inline in the output** — is the whole pattern.

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© Alex Nikulin (Александр Никулин). Original: https://www.alexnix.com/en/articles/typed-reference-composition. Quote only with credit to the author and a link to the original.