| paper | d4-conf-atal-2009-0109 |
| authors | — |
| venue | ? |
| filed under | unclassified |
| judged by | gpt-6-luna / xhigh (triple__luna__xhigh__c6r1) |
| judge confidence | high |
| authors would recognise it | unclear |
The numbered theorems characterize implementability and false-name-proofness, but none states an algorithm, complexity bound, or hardness result. The paper's verification claims give no algorithm or runtime, so there is no eligible computational result to mirror.
fails bit a — no named computational result to mirror
Theorems 1–3 characterize allocation-rule properties, and the paper applies those conditions to example mechanisms; it gives no named computational guarantee for these results.
I can’t make an anchor-supported positive case under the stated rules: the paper has no named computational-complexity result asserting that a problem is in P, NP-hard, FPT, or similar.
Theorem 1, cited from Bikhchandani et al., characterizes implementability by weak monotonicity. Theorem 2, proved here, characterizes false-name-proofness as strategy-proofness plus weak false-name-proofness. Theorem 3, also proved here, characterizes FN-implementability by weak monotonicity and sub-additivity. These are mechanism-design characterizations, not complexity results. The paper says the condition can be used to verify mechanisms, but gives no named result with a runtime bound. Its “computationally feasible” example is prior work, not a result of this paper.
So there are no eligible anchors, no per-anchor continuous problem to state, and no honest A/B/C prediction tied to this paper’s named computational results. That does not show that a continuous-population mirror is impossible; it means this paper supplies no anchor of the kind the assignment requires.
The proponent raises no eligible anchor, and that is decisive for this paper under the stated assignment. Theorem 1 is a cited characterization of strategy-proof implementability; Theorems 2 and 3 characterize false-name-proofness and FN-implementability. None asserts a complexity bound for a computational problem. The paper’s claim that sub-additivity makes verification “easy” has no stated input encoding or runtime bound, and its computationally feasible example is prior work. So there is no named computational result here to mirror.
The strongest salvage would be to pose a new complexity question about recognizing sub-additivity or constructing payments for succinctly represented allocation rules. But the paper specifies no representation for those rules, so that question has no canonical computational form yet. There is also a modelling obstacle: false-name-proofness concerns an individual bidder splitting into several identities, while a bidder has zero mass in a nonatomic population. Preserving that manipulation may require adding atomic agents or changing the auction model; either could be worthwhile research, but it would not mirror a computational result in this paper.
This supports a strong negative verdict on the paper as a source of ChoCo anchors. It does not establish that no useful continuous model of false-name-proof auctions could ever be developed; that broader impossibility would go beyond what the paper supports.
The adversarial triple: the proponent anchors on up to three named results; the opponent sees that case and must defeat every anchor; the judge decides which case convinced it. These are the pipeline’s own outputs, generated by tools/triple_run.py — no human edited them. The paper’s own text is not reproduced here beyond the quoted statement above.