https://www.zhumengyao.com/scidraft/tags/sampling/Recent content in Sampling on SciDraft | A Hugo ThemeHugoenMon, 21 Sep 2026 06:52:00 +0900https://www.zhumengyao.com/scidraft/notes/demo-note-top-p-sampling-pseudocode/Mon, 21 Sep 2026 06:52:00 +0900https://www.zhumengyao.com/scidraft/notes/demo-note-top-p-sampling-pseudocode/<p><strong>Demo note.</strong> This note demonstrates what the <strong>SciDraft</strong> Hugo theme can do for academic and scientific publishing — for research institutions, researchers and students. Its content is demonstration material only: readers should ignore whether the demo content is correct.</p> <p>A language model does not emit a token; it emits a probability for every token in the vocabulary, and something has to choose one. Choosing the single most probable token makes output repetitive, while sampling from the full distribution occasionally picks from its long tail of near-zero probabilities. Nucleus sampling keeps the smallest set of tokens whose combined probability reaches a threshold and samples only from those.</p>