| paper | d4-conf-atal-2016-0221 |
| authors | — |
| venue | ? |
| filed under | unclassified |
| judged by | gpt-6-luna / xhigh (triple__luna__xhigh__c6r1) |
| judge confidence | high |
| authors would recognise it | yes |
Theorem 8 and Corollary 9 characterize manipulation-related properties of aggregation rules, while Proposition 3 is a cited strategyproofness result; none asserts an algorithm, complexity bound, or computational formulation used to compute. The continuous mass-transfer question is a plausible follow-on, and the paper itself points to computational complexity as future work, but it is not a mirror of a computational result in this paper.
fails bit a — no named computational result to mirror
No named computational result is available to mirror. The paper's axiomatic results on single-agent, group, and fragile-coalition manipulation remain outside the computational scope of a result-anchored mirror.
The strongest positive angle I can see is continuous group manipulation in crowdsourced judgment aggregation. Let each type be a complete, consistent judgment set \(J\) on an atomic agenda, and let \(\mu_J\) be the fraction of the population with that truthful judgment set. A manipulation is a transfer \(x_{J,J'}\) of mass from truthful types to reported judgment sets, with total outflow from \(J\) at most \(\mu_J\). For a population quota rule \(F_\alpha\), which accepts a formula when at least an \(\alpha\) fraction reports it, ask whether some positive-mass transfer makes every participating type strictly closer in Hamming distance to the new collective outcome. A large annotation workforce clustered into relatively few judgment types is a plausible high-multiplicity regime.
But that is a proposed new question, not one I can anchor as requested. The paper has no named result asserting a computational complexity or algorithmic classification. The closest results are Theorem 8, proved here, which characterizes group-strategyproofness against up to three manipulators on atomic agendas, and Corollary 9, which derives susceptibility for nontrivial uniform quota rules. They establish axiomatic properties and the existence of manipulation, not the complexity of deciding or finding one. Proposition 3 is a relevant single-agent result, but it is cited from Dietrich and List.
The main weakness in the candidate mirror is that the paper’s witness uses three manipulators. In a population of \(n\), their mass is \(3/n\), which vanishes as \(n\) grows; the paper does not establish that manipulation survives for a positive-mass coalition. So there are zero eligible anchors, and I cannot provide a compliant per-anchor continuous problem. The mass-transfer question is a plausible follow-on, but presenting it as a mirror of a named computational result would overstate the paper.
The strongest case against a *result-anchored* mirror is that the paper supplies no named computational result to continuize. Theorem 8 characterizes an axiomatic property, and Corollary 9 derives susceptibility for quota rules. Proposition 3 is a cited single-agent result, also about strategyproofness rather than computational complexity. None states a complexity bound or gives an algorithmic classification. So the proponent correctly ends with zero eligible anchors.
The best version of their crowdsourcing proposal is still a coherent new problem: put rational mass \(\mu_J\) on complete judgment-set types, allow partial transfers \(x_{J,J'}\) to reports, and ask whether a positive-mass coalition can change a quota outcome so that every participating type strictly improves in Hamming distance. Judgment types are complete for the preferences the paper uses, and crowdsourced annotations can plausibly have high multiplicity. The three-agent witness alone does not defeat this model: it says nothing about whether a positive fraction can manipulate, and the model can ask that directly.
That strength also marks the limit of the negative case. The transfer question is an instance-level computational problem the paper does not analyze. Choosing whether to ask for existence, minimum coalition mass, or minimum reporting cost adds a computational objective or decision task. The paper does point to computational complexity of group manipulation as future work, which supports pursuing such a follow-on. It does not provide a named result whose continuous mirror this would be.
So I can argue that this paper offers no compliant, result-anchored continuous mirror under the stated criteria. I cannot honestly make the broader claim that no worthwhile continuous question exists in any scenario: the crowdsourcing version is plausible, and the paper itself identifies computation as an open direction.
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.