1 citations · 2 across the 19 of their papers we have counts for
23 papers
On the LLM Verification for Argument Graph Generation
Jakub Bąba, Jarosław A. Chudziak
Multi-agent LLM systems can formalize natural-language argumentation end-to-end, turning plain text into structured graphs by classifying components, connecting them with relations…
Coopshift: Post-Training Amplifies The Memory Curse In LLM Cooperation
Jiayuan Liu, Shiyi Du, Tianqin Li +3
How does post-training change cooperation during repeated interaction? Within each of seven released model lineages, we compare pretrained (Base), supervised fine-tuned (SFT), and…
What You Earn from What You Learn: Characterization and Complexity of the Value of Information
Ratip Emin Berker, Ioannis Anagnostides, Emanuel Tewolde +3
We examine the value of information in extensive-form decision problems: the largest multiplicative gain that a decision maker can obtain from an information refinement, taken over…
Do LLMs Take Care of Their Own? Similarity Signals Can Induce Cooperation
Akash Kundu, Emanuel Tewolde, Ratip Emin Berker +2
As LLM-based agents with user-instructed goals are becoming widely deployed, they increasingly encounter each other in strategic interactions, and face challenges of finding mutual…
The Memory Curse: How Expanded Recall Erodes Cooperative Intent in LLM Agents
Jiayuan Liu, Tianqin Li, Shiyi Du +7
Context window expansion is often treated as a straightforward capability upgrade for LLMs, but we find it systematically fails in multi-agent social dilemmas. Across 7 LLMs and 4…
Incentive-Aware Multi-Fidelity Optimization for Generative Advertising in Large Language Models
Jiayuan Liu, Barry Wang, Jiarui Gan +4
Generative advertising in large language model (LLM) responses requires optimizing sponsorship configurations under two strict constraints: the strategic behavior of advertisers an…
CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas
Emanuel Tewolde, Xiao Zhang, David Guzman Piedrahita +2
It is increasingly important that LLM agents interact effectively and safely with other goal-pursuing agents, yet, recent works report the opposite trend: LLMs with stronger reason…
Decision Making under Imperfect Recall: Algorithms and Benchmarks
Emanuel Tewolde, Brian Hu Zhang, Ioannis Anagnostides +2
In game theory, imperfect-recall decision problems model situations in which an agent forgets information it held before. They encompass games such as the ``absentminded driver'' a…
How Many Votes is a Lie Worth? Measuring Strategyproofness through Resource Augmentation
Ratip Emin Berker, Vincent Conitzer, Eden Hartman +2
It is well known, by the Gibbard-Satterthwaite Theorem, that when there are more than two candidates, any non-dictatorial voting rule can be manipulated by untruthful voters. But h…
On the Edge of Core (Non-)Emptiness: An Automated Reasoning Approach to Approval-Based Multi-Winner Voting
Ratip Emin Berker, Emanuel Tewolde, Vincent Conitzer +3
Core stability is a natural and well-studied notion for group fairness in multi-winner voting, where the task is to select a committee from a pool of candidates. We study the setti…
Convergence of Regret Matching in Potential Games and Constrained Optimization
Ioannis Anagnostides, Emanuel Tewolde, Brian Hu Zhang +3
Regret matching (RM) -- and its modern variants -- is a foundational online algorithm that has been at the heart of many AI breakthrough results in solving benchmark zero-sum games…
Designing Rules to Pick a Rule: Aggregation by Consistency
Ratip Emin Berker, Ben Armstrong, Vincent Conitzer +1
Given a set of items and a set of evaluators who all individually rank them, how do we aggregate these evaluations into a single societal ranking? Work in social choice and statist…
Expected Variational Inequalities
Brian Hu Zhang, Ioannis Anagnostides, Emanuel Tewolde +4
Variational inequalities (VIs) encompass many fundamental problems in diverse areas ranging from engineering to economics and machine learning. However, their considerable expressi…
Computing Game Symmetries and Equilibria That Respect Them
Emanuel Tewolde, Brian Hu Zhang, Caspar Oesterheld +2
Strategic interactions can be represented more concisely, and analyzed and solved more efficiently, if we are aware of the symmetries within the multiagent system. Symmetries also…
From Independence of Clones to Composition Consistency: A Hierarchy of Barriers to Strategic Nomination
Ratip Emin Berker, Sílvia Casacuberta, Isaac Robinson +3
We study two axioms for social choice functions that capture the impact of similar candidates: independence of clones (IoC) and composition consistency (CC). We clarify the relatio…
Learning and Computation of -Equilibria at the Frontier of Tractability
Brian Hu Zhang, Ioannis Anagnostides, Emanuel Tewolde +4
-equilibria -- and the associated notion of -regret -- are a powerful and flexible framework at the heart of online learning and game theory, whereby enriching the set of dev…
The Value of Recall in Extensive-Form Games
Ratip Emin Berker, Emanuel Tewolde, Ioannis Anagnostides +2
Imperfect-recall games, in which players may forget previously acquired information, have found many practical applications, ranging from game abstractions to team games and testin…
The Complexity of Computing Robust Mediated Equilibria in Ordinal Games
Vincent Conitzer
Usually, to apply game-theoretic methods, we must specify utilities precisely, and we run the risk that the solutions we compute are not robust to errors in this specification. Ord…
Imperfect-Recall Games: Equilibrium Concepts and Their Complexity
Emanuel Tewolde, Brian Hu Zhang, Caspar Oesterheld +4
We investigate optimal decision making under imperfect recall, that is, when an agent forgets information it once held before. An example is the absentminded driver game, as well a…
Computing Optimal Equilibria in Repeated Games with Restarts
Ratip Emin Berker, Vincent Conitzer
Infinitely repeated games can support cooperative outcomes that are not equilibria in the one-shot game. The idea is to make sure that any gains from deviating will be offset by re…
Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback
Vincent Conitzer, Rachel Freedman, Jobst Heitzig +9
Foundation models such as GPT-4 are fine-tuned to avoid unsafe or otherwise problematic behavior, such as helping to commit crimes or producing racist text. One approach to fine-tu…
Steering No-Regret Learners to a Desired Equilibrium
Brian Hu Zhang, Gabriele Farina, Ioannis Anagnostides +7
A mediator observes no-regret learners playing an extensive-form game repeatedly across rounds. The mediator attempts to steer players toward some desirable predetermined equil…
Game Transformations That Preserve Nash Equilibria or Best-Response Sets
Emanuel Tewolde, Vincent Conitzer
In this paper, we investigate under which conditions normal-form games are (guaranteed to be) strategically equivalent. First, we show for N-player games (N >= 3) that (A) it is NP…