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In district-based multi-party elections, electors cast votes in their respective districts. In each district, the party with maximum votes wins the corresponding seat in the governing body. Election Surveys try to predict the election…

Methodology · Statistics 2023-12-27 Adway Mitra , Palash Dey

In Hotelling's model of spatial competition, a unit mass of voters is distributed in the interval $[0,1]$ (with their location corresponding to their political persuasion), and each of $m$ candidates selects as a strategy his distinct…

Computer Science and Game Theory · Computer Science 2024-05-09 Umang Bhaskar , Soumyajit Pyne

Instant runoff voting (IRV) is an increasingly-popular alternative to traditional plurality voting in which voters submit rankings over the candidates rather than single votes. In practice, elections using IRV often restrict the ballot…

Multiagent Systems · Computer Science 2022-12-06 Kiran Tomlinson , Johan Ugander , Jon Kleinberg

An election is defined as a pair of a set of candidates C=\{c_1,\cdots,c_m\} and a multiset of votes V=\{v_1,\cdots,v_n\}, where each vote is a linear order of the candidates. The Borda election rule is characterized by a vector \langle…

Computational Complexity · Computer Science 2024-05-09 Aizhong Zhou , Fengbo Wang , Jiong Guo

Purpose: Multiwinner voting rules typically require full knowledge of voter preferences, which becomes impractical in large-scale or attention-limited settings. This paper investigates how accurately a winning committee can be approximated…

Computer Science and Game Theory · Computer Science 2026-04-01 Itay Asher Zimet , Shiri Alouf-Heffetz , Nimrod Talmon

We study two-stage committee elections where voters have dynamic preferences over candidates; at each stage, a committee is chosen under a given voting rule. We are interested in identifying a winning committee for the second stage that…

Computer Science and Game Theory · Computer Science 2024-08-21 Valentin Zech , Niclas Boehmer , Edith Elkind , Nicholas Teh

Reinforcement Learning with Verifiable Rewards (RLVR) has achieved great success in developing Large Language Models (LLMs) with chain-of-thought rollouts for many tasks such as math and coding. Nevertheless, RLVR struggles with sample…

Machine Learning · Computer Science 2026-05-15 Kai Yan , Alexander G. Schwing , Yu-Xiong Wang

Runtime Verification (RV) is a lightweight formal technique in which program or system execution is monitored and analyzed, to check whether certain properties are satisfied or violated after a finite number of steps. The use of RV has led…

Formal Languages and Automata Theory · Computer Science 2020-05-13 Zhe Chen , Yunyun Chen , Robert M. Hierons , Yifan Wu

Large Language Model (LLM) agents can increasingly automate complex reasoning through Test-Time Scaling (TTS), iterative refinement guided by reward signals. However, many real-world tasks involve multi-stage pipeline whose final outcomes…

Machine Learning · Computer Science 2025-12-30 Shuyu Gan , James Mooney , Pan Hao , Renxiang Wang , Mingyi Hong , Qianwen Wang , Dongyeop Kang

We survey the design of elections that are resilient to attempted interference by third parties. For example, suppose votes have been cast in an election between two candidates, and then each vote is randomly changed with a small…

Probability · Mathematics 2021-07-13 Steven Heilman

Spoofing-robust automatic speaker verification (SASV) aims to integrate automatic speaker verification (ASV) and countermeasure (CM). A popular solution is fusion of independent ASV and CM scores. To better modeling SASV, some frameworks…

Audio and Speech Processing · Electrical Eng. & Systems 2026-03-19 Kai Tan , Lin Zhang , Ruiteng Zhang , Johan Rohdin , Leibny Paola García-Perera , Zexin Cai , Sanjeev Khudanpur , Matthew Wiesner , Nicholas Andrews

The study of fairness in multiwinner elections focuses on settings where candidates have attributes. However, voters may also be divided into predefined populations under one or more attributes (e.g., "California" and "Illinois" populations…

Computer Science and Game Theory · Computer Science 2022-11-24 Kunal Relia

We develop a model of multiwinner elections that combines performance-based measures of the quality of the committee (such as, e.g., Borda scores of the committee members) with diversity constraints. Specifically, we assume that the…

Computer Science and Game Theory · Computer Science 2017-11-23 Robert Bredereck , Piotr Faliszewski , Ayumi Igarashi , Martin Lackner , Piotr Skowron

Plurality and approval voting are two well-known voting systems with different strengths and weaknesses. In this paper we consider a new voting system we call beta(k) which allows voters to select a single first-choice candidate and approve…

Theoretical Economics · Economics 2020-06-02 Peter Butler , Jerry Lin

Multi-winner voting rules based on approval ballots have received increased attention in recent years. In particular Satisfaction Approval Voting (SAV) and its variants have been proposed. In this note, we show that the winning set can be…

Computer Science and Game Theory · Computer Science 2015-01-12 Haris Aziz , Toby Walsh

We present a substantially expanded version of our tool STV for strategy synthesis and verification of strategic abilities. The new version adds user-definable models and support for model reduction through partial order reduction and…

Logic in Computer Science · Computer Science 2023-10-31 Damian Kurpiewski , Witold Pazderski , Wojciech Jamroga , Yan Kim

Ranked Choice Voting (RCV) adoption is expanding across U.S. elections, but faces persistent criticism for complexity, strategic manipulation, and ballot exhaustion. We empirically test these concerns on real election data, across three…

Computers and Society · Computer Science 2026-02-17 Sanyukta Deshpande , Nikhil Garg , Sheldon H. Jacobson

A crucial part of data analysis is the validation of the resulting estimators, in particular, if several competing estimators need to be compared. Whether an estimator can be objectively validated is not a trivial property. If there exists…

Statistics Theory · Mathematics 2024-05-17 Tino Werner

Autoregressive decoding algorithms that use only past information often cannot guarantee the best performance. Recently, people discovered that looking-ahead algorithms such as Monte Carlo Tree Search (MCTS) with external reward models…

Machine Learning · Computer Science 2025-03-04 Hongming Zhang , Ruixin Hong , Dong Yu

An important question in elections is the determine whether a candidate can be a winner when some votes are absent. We study this determining winner with the absent votes (WAV) problem when the votes are top-truncated. We show that the WAV…

Computer Science and Game Theory · Computer Science 2023-10-12 Qishen Han , Amélie Marian , Lirong Xia
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