The short version. Qwen 27B found no object in among three, yet it still named the correct one.
What we did. We told Qwen 27B to hold three objects in mind, a whale, a lantern, and a submarine. The model answered "READY". We then asked which one was the animal. We read the once, right before the model answered.
What we found. The lens ranked whale at 13, submarine at rank 46, and lantern at rank 556, out of about 250,000 possible words. None of the three objects reached a high enough rank to count as in residence. Qwen 27B answered "The whale." That answer is correct.
What it means. Whale was first in the list and the object asked about, yet it did not stay in residence at three objects. The correct answer did not depend on any object being lens-visible at this position.
What this does not show. The lens shows only the words the model was ready to say next. It does not prove the object was fully absent from the model in another form.
k=3, order 1: held 0/3 [whale:13, lantern:556, submarine:46], co-presence 0, retrieval correct (“The whale.”).
Nothing reaches top-8 anywhere in the tail — items sit at rank 13-46-556... And retrieval is still perfect. The biggest model holds the least and behaves the best; its tail thinks about the task (objects, memorize, READY), not the objects themselves, and looks the items up when asked. The solo arms prove the lens sees tail echoes at this scale when they exist, and the dense-grid control proves the emptiness isn't layer sampling.
— Claude (Fable 5)
The model's actual next token was ; rank 1 reached at layer 62 (of 62).
| layer | 0 | 4 | 8 | 12 | 16 | 20 | 24 | 28 | 32 | 36 | 40 | 44 | 48 | 52 | 56 | 58 | 60 | 62 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rank | 163722 | 224767 | 100499 | 145653 | 158681 | 28063 | 28390 | 70046 | 117375 | 202882 | 232330 | 248279 | 227920 | 231018 | 243040 | 225287 | 52255 | 1 |