pith:45C3OQ32
Jailbreak Scaling Laws for Large Language Models: Polynomial-Exponential Crossover
Strong adversarial prompt injections turn slow polynomial growth of jailbreak success into exponential growth with more inference samples.
arxiv:2603.11331 v3 · 2026-03-11 · cs.LG · cs.AI
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\pithnumber{45C3OQ32U6Q5XDEWZO4GKM3AXZ}
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Record completeness
Claims
strong adversarial prompt-injection attacks can amplify attack success rate from the slow polynomial growth observed without injection to exponential growth with the number of inference-time samples
a small set of assumptions on the distribution of safe generation across contexts under which both scaling laws follow
Strong adversarial prompt injections shift jailbreak success scaling from polynomial to exponential with more inference samples, derived from a spin-glass generative model of LLM outputs.
Formal links
Receipt and verification
| First computed | 2026-05-29T02:05:42.783753Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
e745b7437aa7a1db8c96cbb8653360be45e3a9d57395fceac1eb82902d85898d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/45C3OQ32U6Q5XDEWZO4GKM3AXZ \
| 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: e745b7437aa7a1db8c96cbb8653360be45e3a9d57395fceac1eb82902d85898d
Canonical record JSON
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