geolip-aleph-diffusion

Testable aleph adapters for the geolip diffusion variants — the certified components of the geolip-aleph-qwen text line (frozen-trunk relay adapters with closed-form aleph addressing, zero-init out weight+bias, near-zero gates, bit-exact toggle contract) ported to diffusion trunks. Runner-2 line of the geolip program.

Substrates

variant	trunk	trainer path
SD1.5 core (epred) — primary	stable-diffusion-v1-5/stable-diffusion-v1-5, epsilon objective, natural 77-token prompting	custom beds (this repo, substrate/)
SDXL core (epred) — primary	stabilityai/stable-diffusion-xl-base-1.0	after SD1.5-core certifies; plus the geolip-sdxl-aleph read-only capacity battery
SD15-Lune rectified flow (undertrained exemplar; cheap flow testbed)	AbstractPhil/sd15-flow-lune-json-prompt ckpt-2500 (+ base lune, json-vit)	custom beds (this repo, substrate/)
Anima / Cosmos-Predict2 2B DiT	circlestone-labs/Anima (NC weights — all derived checkpoints NC)	AbstractEyes/diffusion-pipe branch feat/aleph-adapter
Krea 2 Turbo — expansion	krea/Krea-2-Turbo (distilled from krea/Krea-2-Raw, the trainable base; Krea license — check before derived ships)	fork krea2 path; roster entry, beds TBD

Prompting congruency: judged work carries BOTH the json-225 chunked encoding and standard 77-token plain-English prompting (congruency to the natural paradigm).

Sampler of record (Lune family): rectified flow, v = noise − x0, Euler on the SHIFT=2.5-warped sigma grid σ = 2.5u/(1+1.5u), VAE_SCALE 0.18215. Text conditioning is the trainer's 225-token 3-chunk CLIP encoding (encode_clip_225, 227 positions) — never a bare 77-token encode.

Standing rules of the line

• Adapter dtype matches the trunk dtype (fp32 adapters on a low-precision trunk inject fp32 noise; judged gauges still run fp32).
• Pure Adam, weight-decay 0 on adapter paths — never AdamW.
• No comparative selectors (argmax/softmax routing/VQ) anywhere near the aleph; the addresser is the closed-form sinh/cosh read.
• All-adapters-off ≡ frozen trunk bit-exact (code-path-skip toggles), gated before and after every training run.
• Every result reads against the exp000 zero-shot baseline wall below; paired designs with derangement (no-fixed-point) controls; judges self-test on known answers before scoring; 1-seed results ship as candidates.

Baseline wall (exp000)

CLIP-L image↔image cosine, original vs regenerated from the row's own json_prompt (vit_json_prompt for json-vit), conditional vs shuffled-JSON (derangement), n=24 held-out rows of synthetic-object-relations-json, paired seeds, 30 steps, guidance 6.0, fp32 judge features:

model	cond	shuffled	cond − shuffled
json_vit (latest ckpt)	0.8072	0.5568	+0.2504
json_ckpt2500	0.7536	0.5437	+0.2099
base_lune (18765)	0.6347	0.5272	+0.1075

Reading: the json-prompt finetunes carry 2× the base UNet's scene information from structured-JSON conditioning. Caveats: n=24, single seed bank; CLIP-L image-image cosine has a high floor (0.988 for pure-noise pairs on identical resolution) so gaps live in a narrow band — the paired design is load-bearing.

Experiments

exp	question	status
exp000_baselines	zero-shot baseline wall (above)	shipped
exp000b_natural	natural-paradigm wall: format specialization is a double dissociation; SDXL core tops the NL wall	shipped (candidate, s0)
exp001_sd15_relay	relay-all16 vs matched LoRA-r32 vs frozen: relay beats both; LoRA lands below frozen; post-train toggle bit-exact	shipped (candidate, s0)
exp002_sd15_addrcond	addr-cond 4-arm causal: GUIDEPOST with a pulse — inert beside full text (real≈deranged), but the address ALONE steers (+0.029); redesign = complementarity	shipped (candidate, s0)
exp003_sigma_registers	register probe: sigma is the ONLY live axis — caption/type/cond all compress to ≤0; ordering prereg MISS with design consequences	shipped (candidate, s0)
exp004_anima_relay	relays on the 2B DiT via diffusion-pipe (bf16 per dtype law)	staged
exp005_sdxl_tree4a	the SDXL capacity battery (guidepost/scaffold/skeleton)	designed
exp013_blob_flow	CONDITIONING HYPOTHESIS CONFIRMED: same blob coupling, ~200x the eps effect on the flow substrate (−5.9% vs +0.03%); blob supervision belongs on flow/v-pred trunks	shipped (candidate, s0; s1 running)
exp011a_fused_multiband	multiband on REAL fused data: adapters pay 2-3x more; structural story replicates (3/3 surgical, monolith edge persists); blob targets built 100% after a schema lesson	shipped (candidate, s0; s1 running)
exp010_controller	StepGatedSampler ships: controller lifts grounding +0.089 over frozen; monotonic lesion ladder; HIGH lesion 14x LP-dominant (coarse-to-fine confirmed in image space); eps-trained HIGH band concentrates (diversity = open training goal)	shipped (candidate)
exp009_bandroles	role objectives: directional hit 4/4 but noise-adjacent — frequency reweighting too collinear; needs qualitatively different supervision + generation-side gauges (exp010)	shipped (2 seeds + rejudge)
exp008_multiband	band-ASSIGNED experts: mechanism certifies — 3/3 surgical band lesions (50-200x), HIGH-noise band expert wins its band (label-corrected); uniform objective doesn't pay (roles enter exp009)	shipped (candidate, s0; s1 running)
exp006_sd15core_relay	CORE EPRED certification: relay beats frozen (−2.5%) and matched LoRA 2-for-2; grounding gained (+0.036) where LoRA traded it; gates GROW on the core	shipped (candidate, s0)
exp007_amoe_lora	AMoE v1 vs monolith falsifier: falsifier fires — uniform pressure ⇒ flat usage, dispatch pays nothing (Tree-1b law on diffusion); machinery green; next = structural band assignment	shipped (candidate, s0)

Code for each experiment ships in its folder with results.json from the run ledger. Substrate modules in substrate/.