pith:YVLLQUFL
When LLMs Stop Following Steps: A Diagnostic Study of Procedural Execution in Language Models
LLMs lose accuracy on following multi-step arithmetic procedures as length grows from 5 to 95 steps.
arxiv:2605.00817 v2 · 2026-05-01 · cs.CL
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\pithnumber{YVLLQUFLYQ5IARVFRFUNYX4EQH}
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Record completeness
Claims
Across 14 models and 55 datasets, average first-answer accuracy drops from 61% on 5-step procedures to 20% on 95-step procedures.
That the measured accuracy drop reflects failures of procedural fidelity rather than unrelated factors such as context-window limits, arithmetic capability, or prompt formatting.
LLM accuracy on controlled procedural arithmetic drops from 61% at 5 steps to 20% at 95 steps, with failures including skipped steps, premature answers, and hallucinated operations.
Receipt and verification
| First computed | 2026-05-22T01:04:03.936329Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c556b850abc43a8046a58968dc5f8481c1fa3e0421bd2948b31121bbb0fa1dd5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YVLLQUFLYQ5IARVFRFUNYX4EQH \
| 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: c556b850abc43a8046a58968dc5f8481c1fa3e0421bd2948b31121bbb0fa1dd5
Canonical record JSON
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