pith:J3KM5RHE
Resolution Information: Limits of Ambiguity Resolution for Generative Communication
Resolution information reduces to a prior-dependent binary divergence when posteriors are unconstrained, and repeated sampling then drives semantic ambiguity to zero exponentially fast.
arxiv:2605.12800 v1 · 2026-05-12 · cs.IT · math.IT
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Claims
resolution information reduces to a binary divergence that depends only on each region's prior probability. In this case, the shape of the regions is irrelevant. Under repeated sampling, ambiguity decays exponentially with an exponent equal to the resolution information... polytope-type regions can exhibit residual ambiguity that no amount of additional information can remove. These results reveal a fundamental departure from classical channel coding.
The generative representation constrains the posterior family in specific geometric ways (half-spaces resolvable, polytope-type regions leaving irreducible floors) that determine whether asymptotic ambiguity resolution is possible.
Resolution information equals a binary divergence based only on prior probabilities when posteriors are unconstrained, but constrained generative representations can induce irreducible ambiguity floors due to posterior geometry.
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| First computed | 2026-05-18T03:09:12.735140Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/J3KM5RHEISU6ODO52ZWIT7L3FG \
| 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())"
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Canonical record JSON
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