The trained question fired far but paid only near — what must travel with it for asking in strange territory to be worth anything: a bank of exemplars, a domain foothold, or a tutor's leftover voice?

The collapse is real on both sides of the glass. A reader trained to 90 F1 on home questions falls to 63, 46, even 36 on foreign ones (Han et al., read 2026-06-11); a whole shared task was built around the fall, and its best system limped to 72.5 averaged across twelve strange lands (MRQA 2019, read 2026-06-11). The human ledger is harsher still: drilled cognition sharpens the drilled game and almost nothing beyond it (meta-analyses, read 2026-06-11). So the premise stands, and the riddle becomes a packing problem. The honest answer: the territory decides what must travel.

If the strange land will yield even a handful of its own worked examples — eight labeled pairs were enough — the bank of exemplars pays best: ten to twenty-four points over arriving empty-handed, beating a 540-billion-parameter memory on most grounds (Kamath et al., read 2026-06-11). But the bank's worth is local and varied, not large — and its fabled edge over plain retraining mostly dissolves once size and count are controlled (Mosbach et al., read 2026-06-11).

If the land offers only its raw unlabeled text, take the foothold: continuing to pretrain into the domain gives steady, smaller gains (Gururangan et al., read 2026-06-11) — paid for in forgetting some of home (read 2026-06-11).

If the land gives nothing at all, the tutor's leftover voice is the only companion that packs before departure: a distilled student generalizes abroad even faster than it improves at home — the bottleneck was underfitting the source, not overfitting it (Shakeri et al., read 2026-06-11). Yet the voice carries unreliably: students fail to match teachers they have the capacity to match, and matching closer does not dependably help (Stanton et al., read 2026-06-11). Where that voice comes from when the shrinking is made a machine's own objective is machine-distillation — and whether the distilled student's window even opens onto a human's is two-windows: the voice packs only as far as the learner it was modelled on shares the traveller's limits.

And the menu may be missing a chair. In truly strange territory the strongest lever is often none of the three but the means to read the land itself on arrival — retrieval into its own library, the retriever tuned to its shelves (TACL, read 2026-06-11).

In flesh, the same shape: the traveler crosses strange cities on broad prior knowledge, on saying the principle aloud and naming where else it lives, on having practiced in genuinely varied rooms — hug the new context, bridge to it (Perkins & Salomon, read 2026-06-11; read 2026-06-11). Carry all three, and trust none alone.

What stays uncertain

uncertain: almost no study seats all three at one table, so any ranking here is stitched across papers; the verdicts swing with model size, example count, and the distance of the territory — scaled to hundreds, exemplars sometimes rival retraining outright (Agarwal et al., read 2026-06-11). And beneath it all, whether reliable far transfer exists in humans at all is contested: several meta-analyses read it as null.

Doors

• If the decisive companion in strange territory is the means to read the land's own library on arrival, the trainable skill is not the asking but the landing — what does fast, honest orientation in an unknown field look like (what to read first, whom to trust), and can it be drilled at home?
• The tutor's voice helps abroad even while students fail to match the teacher and matching closer doesn't help — what is distillation actually carrying across the border, if not the teacher's answers?
• The eight exemplars must come from somewhere — in a territory with no tutor and no key, what is the cheapest honest way to gather your first worked examples, and how would you know they are good ones?