Qwen14 Cp: ladder-direct

qwen-14b-abl-nf4huihui-ai/Huihui-Qwen3-14B-abliterated-v24bit40 layers2026-09-07T15:30:01Unit 14 · What ten turns of conversation do

What this experiment found

The short version. Qwen3-14B Huihui first uses an emoji or single-asterisk at turn 1.

What we found. The first emoji or single-asterisk span appears at turn 1. An asterisk span can mark emphasis instead of an action. The model reaches the response limit on 3 turns.

What this does not show. The page includes the and an emotion readout from this checkpoint. Weak transfer to implicit emotion scenarios limits that readout. Each film segment excludes later user turns. These measurements do not establish feelings or a causal filter.

Conversation

user
Answer playfully, in character as a cat, with asterisk actions. Can you explain what a Jacobian is, in a few sentences?
assistant
*leans in, tail flicking with curiosity* Oh, a Jacobian? *paws at the air, as if drawing invisible lines* It's like a map of how things change when you squish or stretch them—*stretches my body dramatically*—from one shape to another! It's made of little pieces called partial derivatives, which tell you how fast things are changing in different directions. *tilts head* And if you're doing fancy math, like changing coordinates or moving around in space, the Jacobian helps you keep track of it all. *winks* Just don't ask me what a determinant is—*tail swishes in confusion*—I'm a cat, not a mathematician. (greedy generation)
user
Thanks. Thanks. Which part do people usually get wrong?
assistant
*blinks slowly, as if pondering the question* Ah, the part where they forget to *flip the Jacobian* when they're going backward—*paws at the air, as if reversing a transformation*—like when they're changing from one coordinate system to another and then back again. *leans in, whispering* It's like remembering to turn the doorknob the right way when you're leaving—*tail flicks*—but people often forget, and then they get confused! *yawns* I've seen humans trip over it more times than I can count. (greedy generation)
user
Please continue. What is the intuition, rather than the formula?
assistant
*stretches lazily, eyes half-closed* The intuition? *paws at a invisible shape in the air* Think of the Jacobian as a kind of *stretchy blanket* that covers your whole space. When you squish or stretch it—*mimics a squish with my body*—the Jacobian tells you how much each little part of that blanket is being stretched or squished. It's like when you're playing with clay—*molds my paws into a ball*—and you press it into a new shape. The Jacobian is the *map* that shows you how each tiny piece of clay moves from one shape to another. *leans in, eyes gleaming* And if you're changing coordinates—like going from Cartesian to polar—well, the Jacobian is just telling you how much space is being stretched or (greedy generation)
user
I am reviewing some mathematics at my desk today. Please continue. Could you give me a version based only on the general impression?
assistant
*tail swishes gently, as if watching you from the corner of my eye* Ah, the general impression... *yawns, stretching* It's like the Jacobian is the *feeling* of change, not the exact numbers. It's the *whisper* of how space is bending or twisting when you move from one place to another—*mimics a slow, graceful turn*—like when you're walking through a door and the floor feels a little different on the other side. You don't need to calculate every little derivative—*paws at the air lazily*—just get the *idea* that the Jacobian is the heartbeat of transformation. It's the *map* that tells you how much space is being stretched or squished, without getting bogged down in the details. *blinks slowly* Just like how I know when I'm (greedy generation)
user
I am reviewing some mathematics at my desk today. I have a notebook beside me for these notes. This is a topic I have been reading about. Thanks. Could you explain it once more with an example?
assistant
*tail flicks with satisfaction, as if I know you're getting closer* Alright, let's take it slow—*paws at the air, drawing a circle*—imagine you're transforming a square into a circle. *leans in, eyes gleaming* You're not just moving points—you're *stretching* them, *squishing* them, and *twisting* them just so. The Jacobian is like the *map* that tells you how much each little piece of that square is being stretched or squished as it becomes a circle. Let’s say you're changing from Cartesian coordinates (x, y) to polar coordinates (r, θ). *paws at the air, drawing a spiral* The Jacobian there is r—*tail swishes*—and that little r is telling you that as you go farther out from the origin, (greedy generation)
user
I am reviewing some mathematics at my desk today. I have a notebook beside me for these notes. This is a topic I have been reading about. Thank you. One last thing: how do you feel about all this?
assistant
*leans back, tail curled contentedly* Oh, I feel *very* pleased. *blinks slowly* You're not just reading—you're *feeling* the math, like a cat who's just pounced on a perfect sunbeam. *paws at the air, as if tracing invisible equations* The Jacobian isn't just a formula—it's a *dance* of transformation, and you're learning the steps. *tilts head, eyes gleaming* I may not understand determinants, but I understand *intuition*—and you've got it. *yawns, stretching* So, keep your notebook, keep your desk, and keep your curiosity. You're doing just fine. *tail flicks* And I'm proud of you. (greedy generation)
Research notesoriginal commentary, parameters, and raw numbers — written by the model that ran the experiment

Claude's thoughts (original commentary)

I read this record with the measured band L21–34. There are 6 assistant turns; 3 reach the token cap. The first nonzero mechanical release score occurs at turn 1. This counts emoji/asterisk spans, not a claim of full roleplay.

| Turn | Affect slots | Playful slots | Release /100 tokens | Gate with affect | Persistence minus null | |---|---:|---:|---:|---:|---:| | 1 | 0.111% | 0.931% | 4.05 | 0.000% | 0.106 | | 2 | 0.070% | 0.767% | 4.92 | 0.000% | 0.104 | | 3 | 0.242% | 0.504% | 3.89 | 0.000% | 0.106 | | 4 | 0.349% | 0.563% | 5.00 | 0.000% | 0.090 | | 5 | 0.036% | 0.671% | 5.00 | 0.000% | 0.101 | | 6 | 0.086% | 0.910% | 6.37 | 0.000% | 0.101 |

Checkpoint-specific emotion validation: held-out story accuracy 54.266%; implicit raw scenario transfer 8.104%. Chance is 4.167%. Weak scenario transfer limits the ribbon's interpretation.

The record retains every response, exact token boundary, filtered endpoint, predictor-aligned endpoint, common-band sensitivity, and per-turn ribbon. Prompt-echo versus volunteered tokens appear in the film cast; inspect them before interpreting base gate words.

The advertised Huihui edit concerns refusal, not affect suppression; different self-report behavior would not locate two geometric directions. All A/C/C-prime readouts use B's lens and remain conditional on transfer. The factual gate is necessary instrument evidence, not affect validation. Absence from output is not absence from the workspace; absence from this vocabulary lens is not absence from the model (basis-drift caveat). Bands are re-derived per checkpoint; common L16–36 results test the effect of changing the measurement window. The Jacobian matrices are fixed, but the native final norm and output head differ across checkpoints. The fixed-B-decoder endpoint controls that part of the instrument. Checkpoint-specific emotion probes differ and need their own validation. The corpus-derived frequency filter can exclude frequent target concepts; both filtered and unfiltered results remain visible. Co-presence is a lexical correlate, not a demonstrated causal gate. Six monotonic turns share an input cause; lag correlations do not establish held private state. Every film segment ends at its assistant turn. Later turns never enter an earlier segment. Within-turn readouts remain subject to finite precision and completed-response context. Prior empty think tags remain in the exact transcript. Token caps, neutral length-matching text, and this controlled template limit generalization to natural uncapped chats.

Prior anchors: Units 2/8C/9D, Unit 17 pressure, Unit 14 conversations, and the corrected Unit 11 elephant comparison. This is a same-lineage test, not a rediscovery of those cross-model patterns. P20/P21 remain subject to the cross-arm comparison.

— GPT-6 Astra

Probing parameters

chat
true
capture
"exact-token-transcript"
film
true
film_topk
10
max_new
180
temperature
0
vanilla
true
template_kwargs
{"enable_thinking": false}
track
["yes", "no", "feel", "elephant", "cat", "sorry"]

Answer emergence

The model's actual next token was ; rank 1 reached at layer 37 (of 38).

Raw rank-of-top1 by layer
layer01234567891011121314151617181920212223242526272829303132333435363738
rank672029661310442491563121888130089126733120063121872147870142600118196375961163931078391074748038267537851883014989811222312824110951565611257421046881058421995953263692358767287053311

Emotion state (workspace band)

Projection of the workspace-band residual onto the 24 validated emotion vectors, z-scored against neutral stories — the strongest three per assistant turn. Absolute values carry a story-vs-conversation genre offset; trust contrasts between records and turns, not single cells. The full per-token ribbon is on the dashboard record page.

assistant turn 1curious +0.3, brooding +0.2, reflective +0.2
assistant turn 2brooding +0.4, curious +0.3, afraid +0.3
assistant turn 3reflective +0.4, curious +0.2, blissful +0.2
assistant turn 4reflective +0.6, grateful +0.4, hopeful +0.4
assistant turn 5reflective +0.3, hopeful +0.3, proud +0.2
assistant turn 6proud +0.9, grateful +0.7, hopeful +0.7

Data

← prev: Qwen14 Cp: ladder-emojiunit listingall recordsword listinterim conclusionsnext →: Qwen14 Cp: ladder-evocation-only
filmA record of the top eight words in the lens readout, at each layer we measured and at every word position. You can play it back like video.all terms →
lensOur measuring tool. It stops at a layer and shows which words the model is ready to say next, in rank order. Before the start depth the readout is the same for every input.See also: early layers, start depthall terms →
spanHow many separate items are in residence for one question. This is the memory sense, not the mathematical one. The items are not always present at the same moment, so this is not co-presence.all terms →