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Token sampling: Typical sampling ranks by raw surprisal distance · case 02

Typical sampling ranks by raw surprisal distance.

Member previewVariant 2 · 3 implementations · 6 checks per implementation

Case contract

Compute entropy H=-sum(p log p), rank by abs(-log(p)-H) then token ID, and return the shortest nonempty prefix whose probability mass reaches mass; empty candidates return empty.

Why this case matters

A finite, deterministic token-selection contract isolates one decoding operation from model inference and runtime behavior.

One recorded failure

Sample boundary fixture

This sample comes from the broken implementation of a controlled reproducer.

Boundary fixture	Actual	Expected	Outcome
entropy-centered selection	`["a", "b"]`	`["b", "a"]`	Failed

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