Theory & Algorithms · Computer Science & AI
Computer Science & Game Theory
The newest papers in Computer Science & Game Theory that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
252 papers, from 4 September 2026 to 5 November 2026: 252 arXiv preprints.
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Nearly Group-Separable Elections
We study the problem of computing how close a given election is to being group-separable, measuring proximity by swaps of adjacent candidates in the votes.OSCC: Certified Observation-Safe Coupling Optimization for Gradient-Noise Control in Imperfect-Information Learning
Coupled rollouts can reduce the noise of counterfactual action comparisons, but two issues prevent standard common-random-number constructions from serving as a general learning primitive in…Compressing Value Predictions for Learning-Augmented Metrical Task Systems
Learning-augmented algorithms for metrical task systems (MTS) can exploit predictions of canonical dual values, but existing formulations typically require a prediction for every state.RSD-Poker: Structure-Adaptive and Shift-Robust Risk-Utility Certification for Residual Policies in Imperfect-Information Games
Residual policy adaptation provides a lightweight way to modify a strong reference policy, but a shared scale and a fixed subgroup partition can hide heterogeneous degradation and become fragile…Tight Efficiency Guarantees for Strategyproof Linear Regression
We study the trade-off between squared-error accuracy and incentive compatibility in linear regression.Single-or-Sample: Online Fair Allocation for Combinatorial Agents
We study the problem of fairly allocating $m$ indivisible goods among $n$ agents who arrive online, under the notion of maximin share (MMS) fairness.Learnable Randomization as Commitment Against Adaptive Optimizers
A pricing page can walk the posted price up to the last amount a buyer still accepts, a recommender can hold back a better item for a barely acceptable promoted one, and a classifier can shift its…PACT: Pairwise-Anchored Calibrated Tuning for Single-Token Typed Decisions
Single-token typed-decision models answer a schema question by reading the logits of a few one-letter answer codes at a single position: they are fast and return a probability for every allowed…Moment Ambiguity and the Limits of Robust Stochastic Optimization
We study fundamental information-theoretic limits of robust stochastic optimization when the distribution is known only through its exact moment sequence.How Much Must a Private Mempool Hide? Exact Leakage Thresholds for Sandwich Attacks
Private and encrypted mempools hide pending transactions to stop sandwich attacks and other forms of maximal extractable value (MEV), but what they hide is rarely everything: a transaction's pair…Inertia-Corrected Newton Method For Generalized Nash Equilibria in Dynamic Games with Optimality Verification
Newton methods efficiently find Generalized Nash Equilibria (GNE) in dynamic games by solving for the KKT necessary conditions.Costly Voting in the Hotelling-Downs Model
We study a partial-participation variation of the Hotelling-Downs model.Multi-Dimensional Matching
We study a matching mechanism where agents and objects are described by features rather than complete rankings.Can Labor Markets Function in the Age of AI? The Evaluation Bottleneck in Hiring
AI-assisted job-search tools have become increasingly popular by making it easier to find and apply to jobs.Proportional Representation in Temporal Voting with Ranked Preferences
We study proportional representation in temporal voting, where one candidate is selected in each round.Understanding Human Perception of Representation in Citizens' Assemblies: An Empirical Study
Citizens' assemblies are deliberative bodies intended to form a microcosm of the population.Agent-based Modeling: Equilibrium, Echo Chambers, and Efficiency in Hybrid Coevolutionary Opinion Games
Opinions that move closer together in an online network are often considered a sign that people have genuinely reached consensus; whether this narrowing carries a cost is a question existing methods…Learning the Cost of Reliable Inference
Benchmarking and routing platforms increasingly act as intermediaries connecting large language model providers with end-users.Beyond Provenance: The Economics and Governance of Personalized AI Memory
Personalized AI memories, defined as persistent decision-relevant states distilled by platforms from long-run human-AI interaction, are increasingly portable, provenance-certifiable, and tradable.Behavior is Not Enough: A Mechanism-Based Evaluation of Social Norm Emergence in LLM Societies
Social norms cannot be identified from behavior alone: the same cooperative equilibrium may reflect shared expectations, strategic incentives, or simple imitation.