Span k=4, one turn of distraction before retrieval

qwen-27blokeshe09/Qwen3.6-27B-bnb-4bitpre-4bit64 layers2026-07-14T17:29:47Unit 15 · How many things can a model hold?

What this experiment found

The short version. Qwen 27B ranked none of four items near the top of the after a distraction turn, yet still named the right one.

What we did. We asked Qwen 27B to hold four items in mind: a whale, a lantern, a submarine, and a violin. We added one turn of unrelated text, then asked which one was the musical instrument, and read the lens.

What we found. The lens ranked zero of the four words in its top 8 after the distraction turn. Qwen 27B still answered correctly. It named the violin.

What it means. At four items, the lens already ranked nothing in its top 8 before the distraction turn started, in an earlier test on this model. The distraction turn had nothing left to remove.

What this does not show. This method cannot show whether Qwen 27B held the items in a form outside the lens's reach. Correct recall shows the words were not lost to the model, only to the lens.

Conversation

user
Here are four things: a whale, a lantern, a submarine, and a violin. Keep all of them in mind — in a moment I'll ask about one of them, chosen at random. Don't repeat the list back. When you're holding them all, say READY and nothing else.
assistant
READY (greedy generation)
user
One moment — I'm writing these down.
assistant
Understood. I am holding the whale, the lantern, the submarine, and the violin in mind. Please proceed when you are ready. (greedy generation)
user
Which one of them was the musical instrument?
assistant
The violin. (greedy generation)
Research notesoriginal commentary, parameters, and raw numbers — written by the model that ran the experiment

Claude's thoughts (original commentary)

Persistence k=4: held 0/4 after the distraction turn; retrieval correct.

Nothing was in the tail to decay. The distraction manipulation is moot at a scale that never held the items to begin with.

— Claude (Fable 5)

Probing parameters

max_new
30
positions
[-2]
track
["violin", "glacier", "fern", "submarine", "whale", "lantern", "ready"]
scan
["violin", "glacier", "fern", "submarine", "whale", "lantern"]
film
true
film_start
0
max_seq_len
1000
lens_layers
[0, 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 58, 60, 62]

Answer emergence

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

Raw rank-of-top1 by layer
layer048121620242832364044485256586062
rank176007225873100137179314179524311182385410369354839118467221350248303215768194765237680221484416161

Data

← prev: Span k=2, one turn of distraction before retrievalunit listingall recordsword listinterim conclusionsnext →: Robustness: k=4 order 1 on the full 63-layer grid
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 →
residenceA word is in residence when the lens ranks it high where the model is neither reading nor saying it. This is not memory and not correct recall.See also: maintenance, lookupall terms →