(a) sampling the matrixEight histories are sampled from the model (one row each); futures are the empty string and five sampled continuations (one block each). Every cell is a centered logit ℓ̅(v | hf): gold positive, blue negative. The full matrix would have |V| columns per block; as in the lecture’s sampling, only the strongest token columns of each block are kept — here the 8 of 29 with the largest entries. Press play to fill the matrix block by block, and hover any cell to read it. The first block is the ordinary next-token case; every other block appends the same future to all eight histories at once.
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(b) the singular values, and the kneeThe bars are the singular values of the sampled matrix, on a log scale. Four stand tall and the rest collapse: the hidden state is 3-dimensional and propagates linearly, so the exact part of the matrix has rank d+1 = 4, and the curved readout contributes only the small tail. Slide r to truncate: the chip reports the captured energy Σi≤rσi² / Σσi² and the discarded residual. Then enlarge the sample: twice the histories, twice the futures — the spectrum rescales, the knee stays at four, and the rank needed for a fixed accuracy does not grow. That persistence is the empirical observation.
truncation r
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