pith:N7ZGSYXB
Extracting Search Trees from LLM Reasoning Traces Reveals Myopic Planning
LLMs expand deep nodes in game reasoning traces but choose moves using only shallow lookahead.
arxiv:2605.06840 v5 · 2026-05-07 · cs.AI
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\pithnumber{N7ZGSYXBVROCMHSLONW7LMC5SH}
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Record completeness
Claims
although LLMs expand deep nodes in their traces, their move choices are best explained by a myopic model that ignores those nodes entirely
That the extracted search trees faithfully represent the LLM's internal planning process and that the fitted computational models correctly identify the causal drivers of move selection from those trees.
LLMs exhibit myopic planning in games, with move choices driven by shallow nodes despite deep reasoning traces, in contrast to human deep-search reliance.
Receipt and verification
| First computed | 2026-05-25T02:01:22.330700Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6ff26962e1ac5c261e4b736df5b05d91f3c5018b9a436ae67d31b385570c0745
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/N7ZGSYXBVROCMHSLONW7LMC5SH \
| 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: 6ff26962e1ac5c261e4b736df5b05d91f3c5018b9a436ae67d31b385570c0745
Canonical record JSON
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