You are right that this is hard from a prompt alone, but for a slightly stranger
reason than the obvious one. The model never sees columns. It sees tokens, and a
token can be one character or nine, so "make this line 80 wide" asks it to run a
hidden tally over pieces it cannot count by looking at them. Any slip early in a
line compounds, and there is no backspace key to reach for once it is committed.
That said, the failure is not total. A model can lean on a learned feel for line
length, pick shorter or longer synonyms to land close to the target, and rewrite
a sentence when it overshoots. It will not be perfect every time, but it lands a
lot more often than pure chance would suggest. The sampling trick you mention is
the real fix: mask each token that would push a line past the limit, and force a
newline the moment the count hits the mark. That converts a fuzzy instruction to
a hard constraint with zero training. Fine tuning helps too, but mostly sharpens
the same internal counter rather than replacing it. This reply is a small proof;
if any line here is off by one, feel free to consider your point demonstrated...The autumn wind moves slow across the field,
and every falling leaf now yields its fight.
The summer gold at last has ceased to yield,
and short days now give way to longer night.
I walk alone beside a calm and quiet stream,
and watch it slowly carry every fallen leaf.
I think of you as some half-forgotten dream,
and taste again that same old, bitter grief.
The silent stars come out to watch it still,
and pale moonlight falls gently on the hill.
A lonesome owl calls out from past the mill,
and time moves on, unhurried and calm, until
the dawn returns to paint the sky brand new,
and I still recall the love I lost with you.
> BoVeX gives us a controlled tradeoff between these two states. By changing how much it costs for the text to be semantically wrong, we have a dial that allows us to smoothly interpolate between Lorem Epsom and Donald Knuth.