What was already known
The online problem compares movement cost with an offline optimum that sees the full sequence. Special metrics and larger polylogarithmic upper bounds do not attain the stated general-metric order.
What changed and why it matters
Matches the stated general-metric worst-case order for randomized online k-server.
The AI contribution
OpenAI attributes these manuscripts to its internal model. The entry does not infer individual human contributions beyond that publisher attribution.
Limitations
The adversary is oblivious. Repeated initial positions can require a configuration-dependent additive term. The record is separate from deterministic k-server and does not promise an efficient implementation. Preprint. This is a source-statement and significance assessment, not a proof audit. No independent checking or successful formal compilation is asserted by this entry.
Verification evidence
Evidence labels show what supports the claim. Importance rates its impact if correct.
Author claim
The publisher reports the scoped result. AIProofWatch has not independently validated its correctness.
Accessible artifact / proof
The original written argument is accessible. Availability does not establish a successful proof check or Lean verification.
Correction and publication history
Historical report added after statement, scope, and importance review. No proof audit or formal checking asserted; subscriber alerts disabled.
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