mlsanityData to 7 Oct 2026

Plurality Veto: A Simple Voting Rule Achieving Optimal Metric Distortion

arXiv 2206.07098 ↗First posted 14 Jun 2022cs.GT cs.AIcited by 6

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Abstract (arXiv)

The metric distortion framework posits that n voters and m candidates are jointly embedded in a metric space such that voters rank candidates that are closer to them higher. A voting rule's purpose is to pick a candidate with minimum total distance to the voters, given only the rankings, but not the actual distances. As a result, in the worst case, each deterministic rule picks a candidate whose total distance is at least three times larger than that of an optimal one, i.e., has distortion at least 3. A recent breakthrough result showed that achieving this bound of 3 is possible; however, the proof is non-constructive, and the voting rule itself is a complicated exhaustive search. Our main result is an extremely simple voting rule, called Plurality Veto, which achieves the same optimal distortion of 3. Each candidate starts with a score equal to his number of first-place votes. These scores are then gradually decreased via an n-round veto process in which a candidate drops out when his score reaches zero. One after the other, voters decrement the score of their bottom choice among the standing candidates, and the last standing candidate wins. We give a one-paragraph proof that this voting rule achieves distortion 3. This rule is also immensely practical, and it only makes two queries to each voter, so it has low communication overhead. We also generalize Plurality Veto into a class of randomized voting rules in the following way: Plurality veto is run only for k < n rounds; then, a candidate is chosen with probability proportional to his residual score. This general rule interpolates between Random Dictatorship (for k=0) and Plurality Veto (for k=n-1), and k controls the variance of the output. We show that for all k, this rule has distortion at most 3.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 15 of its 39 references that are in the map. First posted on arXiv 14 Jun 2022.

Builds on

15 of 39 references.

References · 15

  1. 2021Distortion in Social Choice Problems: The First 15 Years and Beyondcited by 16
  2. 2015On Voting and Facility Locationcited by 10
  3. 2020Resolving the Optimal Metric Distortion Conjecturecited by 10
  4. 2022The Metric Distortion of Multiwinner Votingcited by 7
  5. 2016Metric Distortion of Social Choice Rules: Lower Bounds and Fairness Propertiescited by 6
  6. 2019Improved Metric Distortion for Deterministic Social Choice Rulescited by 6
  7. 2019Communication, Distortion, and Randomness in Metric Votingcited by 6
  8. 2015Randomized Social Choice Functions Under Metric Preferencescited by 5
  9. 2018Relating Metric Distortion and Fairness of Social Choice Rulescited by 4
  10. 2019Comparing Election Methods Where Each Voter Ranks Only Few Candidatescited by 4
  11. 2021Metric Distortion Bounds for Randomized Social Choicecited by 4
  12. 2019An Analysis Framework for Metric Voting based on LP Dualitycited by 3
3 more
  1. 2018Random Dictators with a Random Referee: Constant Sample Complexity Mechanisms for Social Choicecited by 2
  2. 2019Approval-Based Elections and Distortion of Voting Rulescited by 2
  3. 2019Favorite-Candidate Voting for Eliminating the Least Popular Candidate in Metric Spacescited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 0; 2025: 2; 2026: 1.

6 papers.