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Related papers: Computing Voting Rules with Improvement Feedback

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We prove that every Condorcet-consistent voting rule can be manipulated by a voter who completely reverses their preference ranking, assuming that there are at least 4 alternatives. This corrects an error and improves a result of [Sanver,…

Computer Science and Game Theory · Computer Science 2017-07-28 Dominik Peters

The pairwise winning indices, computed in the Stochastic Multicriteria Acceptability Analysis, give the probability with which an alternative is preferred to another taking into account all the instances of the assumed preference model…

Optimization and Control · Mathematics 2022-03-29 Sally Giuseppe Arcidiacono , Salvatore Corrente , Salvatore Greco

Collaborative filtering is a popular technique to infer users' preferences on new content based on the collective information of all users preferences. Recommender systems then use this information to make personalized suggestions to users.…

Social and Information Networks · Computer Science 2017-03-06 Ayan Sinha , David F. Gleich , Karthik Ramani

In this paper, we propose a novel ranking framework for collaborative filtering with the overall aim of learning user preferences over items by minimizing a pairwise ranking loss. We show the minimization problem involves dependent random…

Aligning large language models (LLMs) with diverse human preferences is critical for ensuring fairness and informed outcomes when deploying these models for decision-making. In this paper, we seek to uncover fundamental statistical limits…

Computer Science and Game Theory · Computer Science 2026-05-04 Kaizhao Liu , Qi Long , Zhekun Shi , Weijie J. Su , Jiancong Xiao

We investigate approval-based committee voting with incomplete information about the approval preferences of voters. We consider several models of incompleteness where each voter partitions the set of candidates into approved, disapproved,…

Computer Science and Game Theory · Computer Science 2024-08-21 Aviram Imber , Jonas Israel , Markus Brill , Benny Kimelfeld

We propose a novel and efficient algorithm for the collaborative preference completion problem, which involves jointly estimating individualized rankings for a set of entities over a shared set of items, based on a limited number of…

Machine Learning · Statistics 2016-11-16 Suriya Gunasekar , Oluwasanmi Koyejo , Joydeep Ghosh

An important aspect of AI design and ethics is to create systems that reflect aggregate preferences of the society. To this end, the techniques of social choice theory are often utilized. We propose a new social choice function motivated by…

Multiagent Systems · Computer Science 2021-03-02 Gergei Bana , Wojciech Jamroga , David Naccache , Peter Y. A. Ryan

Reinforcement learning with evaluation metrics as rewards is widely used to enhance specific capabilities of language models. However, for tasks such as factually consistent summarisation, existing metrics remain underdeveloped, limiting…

Computation and Language · Computer Science 2026-05-27 Yuxuan Ye , Raul Santos-Rodriguez , Edwin Simpson

We propose a new online learning model for learning with preference feedback. The model is especially suited for applications like web search and recommender systems, where preference data is readily available from implicit user feedback…

Machine Learning · Computer Science 2011-11-04 Pannagadatta K. Shivaswamy , Thorsten Joachims

Proportional ranking rules aggregate approval-style preferences of agents into a collective ranking such that groups of agents with similar preferences are adequately represented. Motivated by the application of live Q&A platforms, where…

Computer Science and Game Theory · Computer Science 2021-05-18 Jonas Israel , Markus Brill

Recent advances in language modeling have underscored the role of preference feedback in enhancing model performance. This paper investigates the conditions under which preference feedback improves parameter estimation in classes of…

Machine Learning · Statistics 2025-05-30 Marc Jourdan , Gizem Yüce , Nicolas Flammarion

Reinforcement learning from human feedback usually models preferences using a reward function that does not distinguish between people. We argue that this is unlikely to be a good design choice in contexts with high potential for…

In this paper we consider the collaborative ranking setting: a pool of users each provides a small number of pairwise preferences between $d$ possible items; from these we need to predict preferences of the users for items they have not yet…

Machine Learning · Statistics 2015-07-17 Dohyung Park , Joe Neeman , Jin Zhang , Sujay Sanghavi , Inderjit S. Dhillon

Conflict of interest is the permanent companion of any population of agents (computational or biological). For that reason, the ability to compromise is of paramount importance, making voting a key element of societal mechanisms. One of the…

Artificial Intelligence · Computer Science 2016-08-10 Arne Recknagel , Tarek R. Besold

Assessors make preference judgments faster and more consistently than graded judgments. Preference judgments can also recognize distinctions between items that appear equivalent under graded judgments. Unfortunately, preference judgments…

Information Retrieval · Computer Science 2021-02-15 Charles L. A. Clarke , Alexandra Vtyurina , Mark D. Smucker

A primary challenge in collective decision-making is that achieving unanimous agreement is difficult, even at the level of criteria. The history of social choice theory illustrates this: numerous normative criteria on voting rules have been…

Theoretical Economics · Economics 2026-01-23 Takahiro Suzuki , Stefano Moretti , Michele Aleandri

We analyse strategic, complete information, sequential voting with ordinal preferences over the alternatives. We consider several voting mechanisms: plurality voting and approval voting with deterministic or uniform tie-breaking rules. We…

Computer Science and Game Theory · Computer Science 2019-04-19 Oren Dean , Yakov Babichenko , Moshe Tennenholtz

We introduce a single-winner perspective on voting on matchings, in which voters have preferences over possible matchings in a graph, and the goal is to select a single collectively desirable matching. Unlike in classical matching problems,…

Computer Science and Game Theory · Computer Science 2026-01-28 Niclas Boehmer , Jessica Dierking

In this paper, we consider large-scale ranking problems where one is given a set of (possibly non-redundant) pairwise comparisons and the underlying ranking explained by those comparisons is desired. We show that stochastic gradient descent…

Optimization and Control · Mathematics 2024-07-04 Benjamin Jarman , Lara Kassab , Deanna Needell , Alexander Sietsema