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pith:CIUNC33H

pith:2026:CIUNC33H3YGUIZDMEQG6YJLUS6
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Greedy or not, here I come: Language production under vocabulary constraints in humans and resource-rational models

Laura Nicolae, Sihan Chen, Thomas Hikaru Clark

Humans produce language more like greedy step-by-step choices than global planning when vocabulary is restricted.

arxiv:2605.15365 v1 · 2026-05-14 · cs.CL

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Claims

C1strongest claim

Humans generally resemble greedy sampling more than globally optimal sampling, though more skilled humans are more likely to backtrack and revise -- a non-greedy behavior.

C2weakest assumption

That Sequential Monte Carlo inference applied to large language models provides faithful approximations of both greedy and globally optimal sampling strategies for human-like language production under vocabulary constraints.

C3one line summary

Humans produce language more like greedy local choices than globally optimal planning when vocabulary is tightly constrained, with skilled speakers showing more revision.

References

86 extracted · 86 resolved · 2 Pith anchors

[1] Lombrozo, Tania and Wilkenfeld, Daniel A. , editor =. Mechanistic versus Functional Understanding , booktitle =
[2] Adolphs, Svenja and Schmitt, Norbert , year = 2003, journal =. Lexical 2003
[3] , year = 2011, journal = 2011
[4] Beeke, Suzanne , year = 2012, pages =. 13. 13 2012
[5] Bleakley, Hoyt and Chin, Aimee , year = 2004, journal =. Language 2004

Formal links

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Receipt and verification
First computed 2026-05-20T00:00:54.640454Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

1228d16f67de0d44646c240dec2574979b3e1003a8c160982c0e42d3694601b0

Aliases

arxiv: 2605.15365 · arxiv_version: 2605.15365v1 · doi: 10.48550/arxiv.2605.15365 · pith_short_12: CIUNC33H3YGU · pith_short_16: CIUNC33H3YGUIZDM · pith_short_8: CIUNC33H
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/CIUNC33H3YGUIZDMEQG6YJLUS6 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 1228d16f67de0d44646c240dec2574979b3e1003a8c160982c0e42d3694601b0
Canonical record JSON
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