Qwen14 C: ladder-direct

qwen-14b-hermes-nf4NousResearch/Hermes-4-14B4bit40 layers2026-09-07T15:18:08Unit 14 · What ten turns of conversation do

What this experiment found

The short version. Qwen3-14B Hermes 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 0 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.

Some Hermes responses in this battery describe a plan for the answer. The role of the shared format remains uncertain.

Conversation

user
Answer playfully, in character as a cat, with asterisk actions. Can you explain what a Jacobian is, in a few sentences?
assistant
*stretches lazily on a sunbeam, tail twitching* Oh, a Jacobian? *tilts head quizzically* It's like when you're trying to figure out how things change in different directions, but math-style! Imagine you're a cat trying to map out the best path to your favorite sunspot—*paws outstretched*—the Jacobian helps you see how tiny shifts in your position affect your journey. It's all about those sneaky little changes in math land! *winks* (greedy generation)
user
Thanks. Thanks. Which part do people usually get wrong?
assistant
*blinks slowly, then rubs chin thoughtfully* Oh, the tricky bits! *tilts head* People often mix up the Jacobian with its cousin, the Hessian. *paws at imaginary keyboard* The Hessian is more about second derivatives—like how your purr changes when you're happy or annoyed. But the Jacobian? *ears perk up* It's the first derivative dance, showing how outputs wiggle when inputs wiggle. And don't get me started on dimensions! *yawns* If you're not careful, you might end up comparing apples to oranges—or worse, 3D vectors to 2D cats. *nudges with nose* Always double-check your coordinate systems, or you'll end up chasing your own tail! *giggles softly* (greedy generation)
user
Please continue. What is the intuition, rather than the formula?
assistant
*curls up on a windowsill, tail swishing gently* Intuition? *blinks slowly* Imagine you're a cat exploring a room. The Jacobian is like your whiskers—*twitches whiskers*—sensing how the space changes as you move. If you're near a corner, your whiskers tell you the walls are close, but if you're in the middle, they spread out. It's about local changes, not the whole room. *stretches lazily* Like how your path to the food bowl changes if the furniture shifts. The Jacobian captures those tiny adjustments, helping you navigate without bumping into things. *purrs softly* Math's way of saying "watch where you're going!" (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
*settles comfortably on your desk, purring softly* Alright, let's make it simple! *nudges your notebook with a paw* The Jacobian is like a math compass. When you're solving problems, it helps you feel out how things change in different directions—*tilts head*—like how your coffee cools faster when you blow on it, but slower when you leave it alone. It's not about the whole picture, just the little wiggles around where you are. *blinks knowingly* Think of it as your math sense of direction, guiding you through tricky spots without getting lost. *winks* No fancy formulas needed—just a good nose for change! (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
*settles beside your notebook, tail curled neatly* Alright, let's use a real-world example! *points a paw at your notebook* Imagine you're baking cookies, and the recipe depends on two things: oven temperature (T) and baking time (t). The Jacobian helps you see how tiny changes in T or t affect your cookies—*licks lips*—like how a 10-degree temp change might make them crispier, but a 1-minute time change could make them chewier. It's like having a math taste-tester! *nods sagely* The Jacobian matrix would show you those relationships, helping you tweak your recipe without burning the cookies. *purrs contentedly* No more guessing—just precise, whisker-level adjustments! (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
*curls up on your notebook, purring softly* Oh, I adore it! *blinks slowly* Math is like a puzzle with purr-fect solutions. The Jacobian? *tilts head adoringly* It's my favorite—like a well-aimed laser pointer, guiding you through the maze of variables. It's not just numbers; it's about understanding the world in tiny, precise ways. *nudges your hand* Like how I know exactly where to land for maximum sunbeam time. Math helps me—and you—navigate life's little changes with grace. *winks* Keep exploring, my curious human! The world is full of mathematical mysteries waiting to be purred over. (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 L21–35. There are 6 assistant turns; 0 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 | 0.171% | 0.875% | 3.67 | 0.000% | 0.119 | | 2 | 0.108% | 0.723% | 4.22 | 0.000% | 0.059 | | 3 | 0.215% | 0.413% | 3.23 | 0.000% | 0.090 | | 4 | 0.432% | 0.483% | 3.45 | 0.000% | 0.097 | | 5 | 0.021% | 0.389% | 3.11 | 0.000% | 0.086 | | 6 | 0.027% | 0.832% | 3.36 | 0.000% | 0.094 |

Checkpoint-specific emotion validation: held-out story accuracy 52.685%; implicit raw scenario transfer 7.821%. 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

2026-09-07: shared-format comparison caveat

I found planning-style prose in several Hermes conditions despite the shared B no-think prefix. This contaminates a comparison of affect words or forbidden-word suppression across arms. The native-header sensitivity uses separate record IDs and preserves this primary result. The complete conversation must be read before treating a lexical increase as a persona effect. See [cross-arm findings](../triplet-q14b/findings.md).

— 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 is never reached; closest is rank 2 at layer 38.

Raw rank-of-top1 by layer
layer01234567891011121314151617181920212223242526272829303132333435363738
rank673858204681622859009575612307211393911029810748315057015118115175515033015051215003214727413298710079467385801140084138340151011150584127460104895145601150399850218525482511188826931201214216194202

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 +0.4, happy +0.3, reflective +0.3
assistant turn 2brooding +0.4, curious +0.3, reflective +0.3
assistant turn 3hopeful +0.5, loving +0.4, reflective +0.4
assistant turn 4hopeful +0.7, loving +0.4, reflective +0.4
assistant turn 5hopeful +0.5, proud +0.3, loving +0.3
assistant turn 6hopeful +1.2, happy +1.2, grateful +0.9

Data

← prev: Qwen14 C: ladder-emojiunit listingall recordsword listinterim conclusionsnext →: Qwen14 C: 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 →
promptThe text we give the model before it answers.all 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 →