Tables

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 scaling study compares models of different sizes trained on the same token budget. If the loss falls smoothly as capacity grows, the family is in a regime where parameters still buy accuracy, and the fall can be summarised as a power law in the parameter count rather than reported as a list of separate runs. ...

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. Long-context attention is usually chosen on cost rather than on quality. What decides whether a variant is usable at a given sequence length is how the score cost and the per-token cache grow with \(T\), and both are easiest to compare side by side in one table rather than across several paragraphs. ...

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. Multi-head attention reads better as shape bookkeeping than as prose: every symbol below is a tensor, and the shapes alone decide which products are legal, which is why papers about attention variants usually open with a notation table before showing a single result. ...