3 citations · 24 across the 52 of their papers we have counts for
10 papers · 1 filter
What Is Lost in Post-Training? Default Collapse and the Loss of In-Context Steerability Across Diverse Perspectives
Jessica Dierking, Itai Shapira, Niclas Boehmer
AI models serving a heterogeneous population must act on the principles appropriate to each user and context. While post-training has been shown to narrow the views large language…
Where Should Society Draw the Line? A Social Choice Approach to Collective Consent
Chris Dong, Sonja Kraiczy, Rohit Vasishta +3
Society constantly has to determine the boundaries of what it deems acceptable, from legislative decisions to the guardrails governing autonomous systems. We initiate the axiomatic…
Approval-Based Multiwinner Voting with Candidate Qualities
Niclas Boehmer, Chris Dong, Luca Kreisel +1
We initiate the study of a new model of approval-based multiwinner voting in which each candidate carries an exogenous quality score, capturing, for instance, the reliability of th…
Fractional Pareto-Optimality in Multiwinner Voting
Patrick Becker, Niclas Boehmer, Fabian Frank +1
Efficiency in multiwinner voting is most naturally captured by Pareto-optimality (PO), yet this notion is computationally and structurally difficult to handle. We therefore study f…
The End Justifies the Mean: A Linear Ranking Rule for Proportional Sequential Decisions
Carmel Baharav, Niclas Boehmer, Bailey Flanigan +1
AI alignment and participatory design motivate a new democratic design problem: how to collectively choose a decision rule to use repeatedly. We study this problem for linear ranki…
Explanation Systems for Approval-Based Multiwinner Voting
Niclas Boehmer, Luca Kreisel, Jannik Peters
In approval-based multiwinner voting, voters express approval preferences over a set of candidates, and the goal is to return a winning committee. This model captures a broad range…
AI of the People, by the People, for the People: A Social Choice Approach to Collective Control of Artificial Intelligence
Paul Anton Bachmann, Niclas Boehmer, Lukas Daniel Klausner +1
With the growing adoption of AI systems, reasoning about how society can exert control over AI becomes an increasingly urgent problem. Existing work on democratic control largely f…
Computational Social Choice: Research & Development
Dorothea Baumeister, Ratip Emin Berker, Niclas Boehmer +7
Computational social choice (COMSOC) studies principled ways to aggregate conflicting individual preferences into collective decisions. In this paper, we call for an increased effo…
Fair Allocation with Initial Utilities
Niclas Boehmer, Luca Kreisel
The problem of allocating indivisible resources to agents arises in a wide range of domains, including treatment distribution and social support programs. An important goal in algo…
Single-Winner Voting on Matchings
Niclas Boehmer, Jessica Dierking
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 collectivel…