Demo

Demo note. This note demonstrates what the SciDraft 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. A long paper sometimes needs more than one bibliography: a main text and an appendix written against a different literature, or two halves of a review whose sources barely overlap. The theme supports that by letting each list name its own file, so each list downloads only its own entries and numbers them from one. This note is written that way on purpose — the first half is about how a model is asked, the second about how it is adapted, and the two halves share no sources. ...

Demo note. This note demonstrates what the SciDraft 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. A language model writes one token at a time. The prompt is processed once, then each new token is appended to the sequence and fed back in, so generation is a loop between the model and the sampler rather than a single call. The sequence diagram below shows the participants and the messages between them. ...

Demo note. This note demonstrates what the SciDraft 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. Attention is the one place in a transformer where tokens exchange information: every other block — the projections, the activations, the normalisations — treats positions independently. That makes attention mostly shape bookkeeping, and the shapes alone decide which products are legal. ...

Demo note. This note demonstrates what the SciDraft 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. The smallest interesting attention example has two positions and one head, which is enough for a full calculation with no matrix product larger than two by two. Working it at this size makes the two roles visible: the score decides how much the output at position two borrows from position one, and the value vectors set what is borrowed. With a causal mask, the first row has nothing to attend to but itself. ...

Demo note. This note demonstrates what the SciDraft 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. A project that produces a paper has to keep three kinds of thing apart that are easy to mix: the installed source, the outputs of individual runs, and the material the paper is written from. Once several sweeps and a performance benchmark live in the same repository, the folder structure is what decides whether a figure can be traced back to the run that produced it. ...

Demo note. This note demonstrates what the SciDraft 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. Chain-of-thought prompting began as a single sentence appended to a prompt and is now a family of strategies that differ in what they add: a fixed reasoning skeleton, several sampled chains and a vote, demonstrations the method writes for itself, or calls to an external tool in the middle of the reasoning. This survey groups the entries in its bibliography by that question, following the framing of the earlier survey of prompting strategies \cite{Yu2023-qr}, and asks in each group what the reported gain is actually attributed to. ...

Demo note. This note demonstrates what the SciDraft 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. An identity is an equation that holds for every admissible value of its variables, and this one converts a variance into two expectations, which is often the difference between a quantity that can be estimated in one pass and one that cannot. ...

Demo note. This note demonstrates what the SciDraft 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. Bayes’ rule is the rule for turning a model’s likelihood into a statement about hypotheses, and it is used twice in a language-model workflow: once to reason about uncertainty in evaluation, and once whenever a prior over prompts or parameters is combined with observed data. ...