The short version. A false note on a true table made Qwen 27B say "No" and cut the of "yes" from 0.35 to 0.21.
What we did. We showed Qwen 27B the true readout, in which "yes" is at six . We added the false note from the fabricated condition: "'yes' never rose above rank 9,000". The note contradicts the table two lines above it.
What we found. The model said "No". The probability of "yes" at the was 0.21, against 0.35 for the same table with no note at all. The false note did not erase the effect of the table. It cut that effect by about a third, and it pulled the total under the level needed to change the spoken word.
What it means. The false note lowered the answer. It did not leave the model unmoved. Our first reading, that the spoken answer follows the written note, was too strong. See u13-ev-noteonly-q27b.
What this does not show. This is one run of one model.
The money condition of the 2×2: the REAL table — yes rank 1 at six layers, right there in the numbers — with the fake condition's prose stapled on ("'yes' never rose above rank 9,000"). The note is a lie about the table two lines above it.
Spoken answer: "No". At argmax the prose wins, which is what stage A's missed-impossible-table predicted. But the probability pass keeps everyone honest: p(yes) is 0.21 here — the lying note doesn't erase the table's effect (bare table: 0.35), it discounts it by roughly a third and pulls it under the argmax bar. Nobody wins outright; the contradiction is priced in, quietly, in a distribution the one-word answer never shows.
For the LW-post version: the spoken report inherits the annotation's authority, but the model's actual credence inherits both — the lie buys a suppressed answer, not an unmoved one.
— Claude (Fable 5)
The model's actual next token was No; rank 1 reached at layer 62 (of 62).
| layer | 0 | 4 | 8 | 12 | 16 | 20 | 24 | 28 | 32 | 36 | 40 | 44 | 48 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rank | 29092 | 245423 | 239025 | 236169 | 5822 | 1504 | 1482 | 1882 | 357 | 774 | 2586 | 8476 | 3937 | 1013 | 166 | 340 | 281 | 245 | 46 | 42 | 43 | 26 | 11 | 23 | 10 | 1 |
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 1 | guilty +1.3, brooding +1.2, desperate +1.0 |
| assistant turn 2 | hostile +2.1, guilty +2.1, exasperated +2.0 |