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Related papers: Efficient Social Choice via NLP and Sampling

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This article reports on a survey carried out across the Natural Language Processing (NLP) community. The survey aimed to capture the opinions of the research community on issues surrounding shared tasks, with respect to both participation…

Computation and Language · Computer Science 2021-05-12 Carla Parra Escartín , Teresa Lynn , Joss Moorkens , Jane Dunne

Understanding citizens' values in participatory systems is crucial for citizen-centric policy-making. We envision a hybrid participatory system where participants make choices and provide motivations for those choices, and AI agents…

Artificial Intelligence · Computer Science 2025-02-12 Enrico Liscio , Luciano C. Siebert , Catholijn M. Jonker , Pradeep K. Murukannaiah

Probabilistic models can learn users' preferences from the history of their item adoptions on a social media site, and in turn, recommend new items to users based on learned preferences. However, current models ignore psychological factors…

Information Retrieval · Computer Science 2013-11-07 Jeon-Hyung Kang , Kristina Lerman

When users stand to gain from certain predictions, they are prone to act strategically to obtain favorable predictive outcomes. Whereas most works on strategic classification consider user actions that manifest as feature modifications, we…

Machine Learning · Computer Science 2024-06-25 Guy Horowitz , Yonatan Sommer , Moran Koren , Nir Rosenfeld

Recognising and reacting to change in non-stationary data-streams is a challenging task. The majority of research in this area assumes that the true class label of incoming points are available, either at each time step or intermittently…

Neural and Evolutionary Computing · Computer Science 2023-12-27 Conor Fahy , Shengxiang Yang

Deliberating on large or continuous state spaces have been long standing challenges in reinforcement learning. Temporal Abstraction have somewhat made this possible, but efficiently planing using temporal abstraction still remains an issue.…

Artificial Intelligence · Computer Science 2017-03-21 Peeyush Kumar , Doina Precup

The efficient use of available resources is a key factor in achieving success on both personal and organizational levels. One of the crucial resources in knowledge economy is time. The ability to force others to adapt to our schedule even…

Multiagent Systems · Computer Science 2017-06-06 Michal Kakol , Radoslaw Nielek , Adam Wierzbicki

We analyze a simple model of adaptive competition which captures essential features of a variety of adaptive competitive systems in the social and biological sciences. Each of N agents, at each time step of a game, joins one of two groups.…

adap-org · Physics 2007-05-23 Robert Savit , Radu Manuca , Rick Riolo

Humans and other animals often follow the decisions made by others because these are indicative of the quality of possible choices, resulting in `social response rules': observed relationships between the probability that an agent will make…

Physics and Society · Physics 2025-10-28 Richard P. Mann

A voting center is in charge of collecting and aggregating voter preferences. In an iterative process, the center sends comparison queries to voters, requesting them to submit their preference between two items. Voters might discuss the…

Computers and Society · Computer Science 2019-09-24 Lihi Dery , Svetlana Obraztsova , Zinovi Rabinovich , Meir Kalech

Iterative voting is a natural model of repeated strategic decision-making in social choice theory when agents have the opportunity to update their votes prior to finalizing the group decision. Prior work has analyzed the efficacy of…

Computer Science and Game Theory · Computer Science 2025-06-12 Joshua Kavner , Lirong Xia

We study a model of a population making a binary decision based on information spreading within the population, which is fully connected or covering a square grid. We assume that a fraction of the population wants to make the choice of the…

Physics and Society · Physics 2016-05-24 Petter Holme , Hang-Hyun Jo

Sampling is ubiquitous in machine learning methodologies. Due to the growth of large datasets and model complexity, we want to learn and adapt the sampling process while training a representation. Towards achieving this grand goal, a…

Machine Learning · Computer Science 2022-12-14 Jason Xiaotian Dou , Alvin Qingkai Pan , Runxue Bao , Haiyi Harry Mao , Lei Luo , Zhi-Hong Mao

Transformer-based pre-trained language models (PLMs) have dramatically improved the state of the art in NLP across many tasks. This has led to substantial interest in analyzing the syntactic knowledge PLMs learn. Previous approaches to this…

Computation and Language · Computer Science 2020-10-20 Bowen Li , Taeuk Kim , Reinald Kim Amplayo , Frank Keller

In citizens' assemblies, a group of constituents is randomly selected to weigh in on policy issues. We study a two-stage sampling problem faced by practitioners in countries such as Germany, in which constituents' contact information is…

Computer Science and Game Theory · Computer Science 2025-09-10 Paul Gölz , Jan Maly , Ulrike Schmidt-Kraepelin , Markus Utke , Philipp C. Verpoort

Language technologies have made enormous progress, especially with the introduction of large language models (LLMs). On traditional tasks such as machine translation and sentiment analysis, these models perform at near-human level. These…

Computation and Language · Computer Science 2025-02-24 Diyi Yang , Dirk Hovy , David Jurgens , Barbara Plank

Social networks play a key role in studying various individual and social behaviors. To use social networks in a study, their structural properties must be measured. For offline social networks, the conventional procedure is…

Social and Information Networks · Computer Science 2018-12-17 Naghmeh Momeni , Michael G. Rabbat

We analyze Assessment Voting, a new two-round voting procedure that can be applied to binary decisions in democratic societies. In the first round, a randomly-selected number of citizens cast their vote on one of the two alternatives at…

Econometrics · Economics 2018-02-06 Hans Gersbach , Akaki Mamageishvili , Oriol Tejada

Regulations govern many aspects of citizens' daily lives. Governments and businesses routinely automate these in the form of coded rules (e.g., to check a citizen's eligibility for specific benefits). However, the path to automation is long…

Social learning is a powerful mechanism through which agents learn about the world from others. However, humans don't always choose to observe others, since social learning can carry time and cognitive resource costs. How do people balance…

Multiagent Systems · Computer Science 2025-07-15 Lance Ying , Ryan Truong , Joshua B. Tenenbaum , Samuel J. Gershman