ICML 2026PastTheory
New Frontiers in Game-Theoretic Learning - NExT-Game
ICML 2026 Workshop
- Submission deadline
- May 13, 2026, 12:00 UTCOpenReview-synced 2026-05-13 12:00 UTC (as of 2026-06-23) — extensions on OpenReview are applied automatically; verify on the website.
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (64)
Fetched from OpenReview (v2) on 2026-06-10.
A Causal Approach to Game Theory
A Minimal Decision Capacity Threshold Prevents Catastrophic Exploitation in Self-Play RL
Adversarial Training with Large Step Sizes: Implicit Bias and Evolution of Sharpness
AgentSociety: Incentivizing Agentic Social Intelligence
AlphaZero in Sparsely Rewarded Games: Limits and Auxiliary Supervision
Attention as Natural Gradient: In-Context Mirror Descent for Opponent Modelling
Bayesian Persuasion with a Risk-Conscious Receiver
Bellman-Local Lyapunov Barriers for Exact Stationary Nash Learning in Discounted Perfect-Information Stochastic Games
Beyond Scalar Rewards: Dense Feedback for LLM Policy Synthesis in Sequential Social Dilemmas
Beyond Task Success: Evaluating Cooperation in LLM-Based Multi Agent Systems
Bridging Game Theory and Transformer Routing: Mean Field Equilibria for Mixture of Experts
COMRAD: A Benchmark for Embodied Cooperative Multi-Agent Reinforcement Learning
Designing Training Objectives for Iterative Reasoning Agents: Dense Supervision as an Adaptive Mechanism
Do Prompted Strategic Personas Influence Decision Making in Large Language Models? A Chess-Based Experimental Study
Dynamics of Adversarial Attacks on Large Language Model-Based Search Engines
EMAgnet: Parameter-Space EMA Regularization for Policy Gradient Self-Play in Large Games
EngineLab: Evaluating Strategic Generalization Under Rule Shifts
Equilibrium Selection in Multi-Agent Policy Gradients via Opponent-Aware Basin Entry
Failure Modes in AI Retraining Dynamics
Fair Robust Strategic Classification under Decision-Dependent Cost Uncertainty
First-Order Efficiency for Probabilistic Value Estimation via A Statistical Viewpoint
From Risk Scoring to Risk Allocation: A Density-Driven Framework for Diverse Monitoring in Multi-Agent Systems
GT-HarmBench: Benchmarking AI Safety Risks Through the Lens of Game Theory
In-Context Credit Assignment via the Core
Incentive design in sequential statistical protocols
Kantian Equilibrium in the Age of Multi-Agent Systems
Learned Coordination Conventions in Cooperative MARL: Measuring the Translation Gap Between Theory-Informed Roles and Learned Routing
Learning Bidding Strategies for Karma Economies in Realistic Traffic Settings with Multi-Agent Reinforcement Learning
Learning to Diffuse: Mechanism Design in Social Networks with Information Propagation Costs
Learning to Mediate Equilibrium Selection in LLM Games
LERA: LLM-Enhanced RAG for Ad Auction in Generative Chatbots
MafiaPersona: A Multi-Agent Adversarial Benchmark for Evaluating Persona Persistence in Large Language Models
Markov Chain from Human Feedback
Mechanism Design for Multi-Agent Alpha Discovery: Optimizing Agent Distribution in Heterogeneous LLM Markets
Multi-Agent Reinforcement Learning of Karma Bidding Strategies
Nash Bargaining for Gate-Free Mixture-of-Experts
Neural Algorithmic Reasoning for Nash Equilibrium
No-Regret Learning in Bayesian Stackelberg Games with Unknown Follower Types
Non-Linear Strategic Classification Made Practical
Opponent Modeling and Value of Information in Deep Reinforcement Learning for the Iterated Prisoner’s Dilemma
Optimism as a Vulnerability: Deceptive Stackelberg Control of UCB Bandit Followers
PALS: Preference-guided Active Automata Learning for Symbolic Reinforcement Learning in Games
Parametric Open Source Games
Poker Arena: Multi-Axis Profiling of Strategic Reasoning and Memory in LLMs
PoolBench:Benchmarking Large Language Models on Continuous Physical Action Selection in Eight-Ball Pool
Position: Alignment Needs Rule-Class Routing Before Preference Learning
Power and Limitations of Aggregation in Compound AI Systems
Preference-Based Distributed Welfare Maximization: A Game-Theoretic Approach
Scaling Laws for Strategic Interactions
Seeing Through Distractions: Stable Attribution via the Core
Self-Play Reinforcement Learning under Imperfect Information in Big 2
Sequential Minimax Games as Stacked Martingale Optimal Transport
Signaling in Data Markets via Free Samples
Stackelberg Mean-Field Games for Adaptive Cancer Therapy
Strategic Testing in Games
Superhuman AI for Generals.io Using Self-Play Reinforcement Learning
The Clone Game: Strategic Ecology for Monoculture-Resistant AI Agents
The computational complexity of computing refunds
The Cost of Blind Confidence: Opponent Modeling under Imperfect Information
The Price of Over-Delegation: Stackelberg Liability Design for Agentic AI Handoffs
The Symmetry Trap: Parametric Equilibria and the Welfare Cost of Architectural Monoculture
Towards Learning Representations of Policies in Two-Player Zero-Sum Games
When Agents Lie: Premeditation, Persistence, and Exploitation in Repeated Games
Zero Shot Coordination for Sparse Reward Tasks with Diverse Reward Shapings