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We consider the distributed single-winner metric voting problem on a line, where agents and alternative are represented by points on the line of real numbers, the agents are partitioned into disjoint districts, and the goal is to choose a…

Computer Science and Game Theory · Computer Science 2023-01-05 Alexandros A. Voudouris

We propose a new single-winner election method ("Schulze method") and prove that it satisfies many academic criteria (e.g. monotonicity, reversal symmetry, resolvability, independence of clones, Condorcet criterion, k-consistency,…

Computer Science and Game Theory · Computer Science 2025-10-28 Markus Schulze

To aggregate rankings into a social ranking, one can use scoring systems such as Plurality, Veto, and Borda. We distinguish three types of methods: ranking by score, ranking by repeatedly choosing a winner that we delete and rank at the…

Computer Science and Game Theory · Computer Science 2022-09-20 Niclas Boehmer , Robert Bredereck , Dominik Peters

In ranked-choice elections voters cast preference ballots which provide a voter's ranking of the candidates. The method of ranked-choice voting (RCV) chooses a winner by using voter preferences to simulate a series of runoff elections. Some…

General Economics · Economics 2023-06-12 Mallory Dickerson , Erin Martin , David McCune

The goal of this paper is to propose and study properties of multiwinner voting rules which can be consider as generalisations of single-winner scoring voting rules. We consider SNTV, Bloc, k-Borda, STV, and several variants of…

Computer Science and Game Theory · Computer Science 2015-06-10 Edith Elkind , Piotr Faliszewski , Piotr Skowron , Arkadii Slinko

Video reasoning has advanced with large multimodal models (LMMs), yet their inference is often a single pass that returns an answer without verifying whether the reasoning is evidence-aligned. We introduce Reinforce to Learn, Elect to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Songyuan Yang , Weijiang Yu , Jilin Ma , Ziyu Liu , Guijian Tang , Wenjing Yang , Huibin Tan , Nong Xiao

Large Language Models (LLMs) exhibit systematic biases across demographic groups. Auditing is proposed as an accountability tool for black-box LLM applications, but suffers from resource-intensive query access. We conceptualise auditing as…

Machine Learning · Computer Science 2026-01-07 David Hartmann , Lena Pohlmann , Lelia Hanslik , Noah Gießing , Bettina Berendt , Pieter Delobelle

Runtime assurance (RTA) addresses the problem of keeping an autonomous system safe while using an untrusted (or experimental) controller. This can be done via logic that explicitly switches between the untrusted controller and a safety…

Logic in Computer Science · Computer Science 2023-06-08 Kristina Miller , Christopher K. Zeitler , William Shen , Mahesh Viswanathan , Sayan Mitra

We propose a new single-winner voting system using ranked ballots: Stable Voting. The motivating principle of Stable Voting is that if a candidate A would win without another candidate B in the election, and A beats B in a head-to-head…

Theoretical Economics · Economics 2023-02-14 Wesley H. Holliday , Eric Pacuit

Multiple Choice Question (MCQ) answering is a widely used method for evaluating the performance of Large Language Models (LLMs). However, LLMs often exhibit selection bias in MCQ tasks, where their choices are influenced by factors like…

Computation and Language · Computer Science 2025-12-01 Blessed Guda , Lawrence Francis , Gabrial Zencha Ashungafac , Carlee Joe-Wong , Moise Busogi

STV and ranked pairs (RP) are two well-studied voting rules for group decision-making. They proceed in multiple rounds, and are affected by how ties are broken in each round. However, the literature is surprisingly vague about how ties…

Artificial Intelligence · Computer Science 2019-01-29 Jun Wang , Sujoy Sikdar , Tyler Shepherd , Zhibing Zhao , Chunheng Jiang , Lirong Xia

Adaptive prompt and program search makes LLM evaluation selection-sensitive. Once benchmark items are reused inside tuning, the observed winner's score need not estimate the fresh-data performance of the full tune-then-deploy procedure. We…

Machine Learning · Statistics 2026-05-08 Yang Xu , Jiefu Zhang , Haixiang Sun , Zihan Zhou , Tianyu Cao , Vaneet Aggarwal

Multi-task learning (MTL) seeks to improve the generalized performance of learning specific tasks, exploiting useful information incorporated in related tasks. As a promising area, this paper studies an MTL-based control approach…

Systems and Control · Electrical Eng. & Systems 2024-08-01 Andres Arias , Chuangchuang Sun

Justified representation (JR) and extended justified representation (EJR) are well-established proportionality axioms in approval-based multiwinner voting. Both axioms are always satisfiable, but they rely on a fixed quota (typically Hare…

Computer Science and Game Theory · Computer Science 2026-02-18 Patrick Becker , Fabian Frank

We study the performance of voting mechanisms from a utilitarian standpoint, under the recently introduced framework of metric-distortion, offering new insights along three main lines. First, if $d$ represents the doubling dimension of the…

Computer Science and Game Theory · Computer Science 2022-03-25 Ioannis Anagnostides , Dimitris Fotakis , Panagiotis Patsilinakos

Reinforcement Learning (RL) bears the promise of being a game-changer in many applications. However, since most of the literature in the field is currently focused on opaque models, the use of RL in high-stakes scenarios, where…

Machine Learning · Computer Science 2025-01-22 Leonardo Lucio Custode , Giovanni Iacca

A boardroom election is an election that takes place in a single room -- the boardroom -- in which all voters can see and hear each other. We present an initial exploration of boardroom elections with ballot privacy and voter verifiability…

Cryptography and Security · Computer Science 2021-03-19 Enka Blanchard , Ted Selker , Alan T. Sherman

Algorithms for resolving majority cycles in preference aggregation have been studied extensively in computational social choice. Several sophisticated cycle-resolving methods, including Tideman's Ranked Pairs, Schulze's Beat Path, and…

Computer Science and Game Theory · Computer Science 2025-12-30 Wesley H. Holliday , Milan Mossé , Chase Norman , Eric Pacuit , Cynthia Wang

Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as a core paradigm for enhancing the reasoning capabilities of Large Language Models (LLMs). To address the lack of verification signals at test time, prior studies…

Computation and Language · Computer Science 2025-10-17 Wenkai Yang , Weijie Liu , Ruobing Xie , Yiju Guo , Lulu Wu , Saiyong Yang , Yankai Lin

We present Phrase-Verified Voting, a voter-verifiable remote voting system assembled from commercial off-the-shelf software for small private elections. The system is transparent and enables each voter to verify that the tally includes…

Cryptography and Security · Computer Science 2021-03-15 Enka Blanchard , Ryan Robucci , Ted Selker , Alan Sherman