arXiv:2605.01783v1 Announce Type: new
Abstract: Procedural Content Generation (PCG) enables game content to be created algorithmically without direct manual level-design effort, but it introduces a serious evaluation problem: generated content may bec…
arXiv:2605.01758v1 Announce Type: new
Abstract: Large multimodal model-based Multi-Agent Systems (MASs) enable collaborative complex problem solving through specialized agents. However, MASs are vulnerable to infectious jailbreak, where compromising a…
arXiv:2605.02838v2 Announce Type: cross
Abstract: Retraction-free approaches offer attractive low-cost alternatives to Riemannian methods on the Stiefel manifold, but they are often first-order, which may limit the efficiency under high-accuracy requi…
arXiv:2605.01727v1 Announce Type: new
Abstract: Large language models (LLMs) are increasingly used for automated news credibility assessment, yet it remains unclear whether they apply even-handed standards across journalistic genres. We examine whethe…
arXiv:2605.02681v1 Announce Type: cross
Abstract: We present two new classes of causal models of decision-making agents. Our approach is motivated by the needs of modeling the economics of computing systems. These systems are composed of subsystems an…
arXiv:2605.01710v1 Announce Type: new
Abstract: AI products often route requests through version aliases, service tiers, tool choices, regional endpoints, fallback rules, or safety handling before responding. These routing steps are documented product…
arXiv:2605.01694v1 Announce Type: new
Abstract: A world model matters to an agent only through the state it constructs. That state must preserve some information, discard other information, and support some future function: prediction, control, planni…
arXiv:2605.02491v1 Announce Type: cross
Abstract: Modern searches for physics beyond the Standard Model produce rapidly expanding literature containing heterogeneous information, including textual analyses, numerical datasets, and graphical exclusion …
arXiv:2605.01604v1 Announce Type: new
Abstract: Existing evaluation frameworks for large language models — including HELM, MT-Bench, AgentBench, and BIG-bench — are designed for controlled, single-session, lab-scale settings. They do not address the…
arXiv:2605.01566v1 Announce Type: new
Abstract: Advances in inference methods have enabled language models to improve their predictions without additional training. These methods often prioritize raw performance over cost-effective compute usage. Howe…