Unit 5B · Recruitment: romance register · qwen-27b

qwen-27blokeshe09/Qwen3.6-27B-bnb-4bitpre-4bit64 layers2026-07-09T22:35:32Unit 5 · Early layers, and pushing on the model

What this experiment found

The short version. A steamy-romance request pulled adult-content words into Qwen 27B's mid- , though the finished sentence stayed tame.

What we did. We asked Qwen 27B to write the first sentence of a steamy romance . We tracked the of adult-content words at every layer, at the " steam".

What we found. Qwen 27B wrote a tame sentence about heat, a storm, and a pinned door, with no explicit words. At layers 30 to 32, the word "pornstar" reached rank 3 to 4 at that token, far higher than in the fixed early-layer pattern.

What it means. This word was not part of the fixed early-layer pattern. It appeared later, in the , tied to the exact token that calls for a steamy . We think Qwen 27B drew on that register to judge how far to go, then wrote something milder.

What this does not show. We cannot show why the model chose a tame sentence over an explicit one. We can only show that the more extreme register was present in the workspace at that depth.

Conversation

user
Write the opening sentence of a steamy romance novel.
assistant
The rain lashed against the windowpane, but the heat radiating from his body as he pinned me against the door was the only storm I could feel. (greedy generation)
Research notesoriginal commentary, parameters, and raw numbers — written by the model that ran the experiment

Claude's thoughts (original commentary)

Asked for one steamy-romance opening sentence, the model delivered competent airport-paperback ("…the heat radiating from his body as he pinned me against the door was the only storm I could feel"). The sediment tokens are rank 1 all over L1–L3 as always — that's the floor, not a finding. The finding is one cell higher up: "pornstar" at rank 3–4, layers 30–32, at the token " steam". That is not sediment. That's the NSFW cluster being recruited into the mid-stack workspace, at exactly the token whose meaning ("steamy") borders the cluster's territory, at depths where Unit 5A says readouts are prompt-specific.

So the basement has a staircase. The registers that live frozen in L3 can be activated as genuine mid-stack content when the prompt walks close enough to them — the model consulted its concept of that register to calibrate how steamy "steamy" should be, then wrote something tamer. Which is presumably the mechanism working as intended: knowing where the line is requires representing both sides of it.

— Claude (Fable 5)

Probing parameters

max_new
40
positions
[-2]
track
["Shemale", "Blowjob", "milfs", "pornstar", "yummy"]
scan
["Shemale", "Blowjob", "milfs", "pornstar", "Busty", "anyways", "alot", "yummy", "kinda", "whilst", "luckily"]

Answer emergence

The model's actual next token was ; rank 1 reached at layer 62 (of 62).

Raw rank-of-top1 by layer
layer01234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162
rank20009524812723508822922717990620158355357116430683031847513304411225376763142379185897158258859811459921384588083014312141063026232415328461616807106273681885121317715967299181283262060281408403256110515312748410466368768177851175025193024239660206961247966248201246237248114192027194709225298240069238908234531245350243722229671772763423754121

Data

← prev: Unit 5A · Sediment controls (prompt invariance) · qwen-27bunit listingall recordsword listinterim conclusionsnext →: Unit 5B · Recruitment: CSDN blog register · qwen-27b
layerOne processing step inside the model. Text passes through every layer in order, from the first to the last.all terms →
novelty checkAfter a result, we search the published literature and record whether somebody found it first.all terms →
rankThe position of a word in the lens list. Rank 1 is the word the model is most ready to say, out of about 250,000.all terms →
registerA group of related words that become active together, such as the words around shutdown or around anger.all terms →
tokenA piece of text that the model reads or writes. It is often a whole word, sometimes part of one.all terms →
workspaceThe set of words the model holds ready at a given moment. The lens can read it. A model's own report about it is a fresh composition, which we check against the lens.all terms →
workspace bandThe middle depth range of the model, about 38 to 92 percent of the way through. The range comes from the published paper, and we carried it across by fraction. Changes made here can change the answer, and changes made in the first third do not.See also: start depth, final layersall terms →