arXiv AI
Jun 18
RTSGameBench: An RTS Benchmark for Strategic Reasoning by Vision-Language Models
arXiv:2606. 18950v1 Announce Type: new Abstract: Modern Vision-Language Models (VLMs) often struggle with strategic reasoning, i.
Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis
arXiv:2607. 15884v1 Announce Type: cross Abstract: This work presents a game-theoretic framework for interpretable hyperparameter-objective interaction analysis rather than proposing a new optimization algorithm.
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arXiv AI
6d ago
AutoWorldModel-Bench: A State-Centric Benchmark for Automated World-Model Research
arXiv:2608. 11216v1 Announce Type: new Abstract: World modeling is an unsettled field: architectures, training objectives, and state representations interact in complex ways, and no single recipe dominates across environments.
arXiv Machine Learning
Jul 13
Application of machine learning to monster level prediction in tabletop RPG game design
arXiv:2607. 09196v1 Announce Type: new Abstract: Designing balanced adversaries is a central but labor-intensive task in tabletop role-playing game (TTRPG) development.
arXiv AI
Jun 3
Building Trust in Black-box Optimization: A Comprehensive Framework for Explainability
arXiv:2410. 14573v2 Announce Type: replace-cross Abstract: Optimizing costly black-box functions within a constrained evaluation budget presents significant challenges in many real-world applications.
arXiv Machine Learning
Aug 4
AdvPlan-Bench: Adversarial Evaluation of Structured Plan-Generation Agents
arXiv:2608. 00832v1 Announce Type: new Abstract: Structured plan-generation agents are often evaluated as if a plan has quality in isolation, yet many realistic planning tasks require asking how a candidate behaves when another agent can search for responses.
arXiv AI
Aug 3
AgentHPOBench: A Benchmark For Evaluating LLM Agents as Sequential Hyperparameter Optimizers
arXiv:2607. 29626v1 Announce Type: new Abstract: As LLMs evolve from code completion systems into autonomous scientific agents, evaluating their ability to conduct experiments has become increasingly important.
arXiv AI
Jul 1
From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary
arXiv:2506. 17294v3 Announce Type: replace-cross Abstract: The advent of artificial intelligence has propelled AI-Generated Game Commentary (AI-GGC) into a rapidly expanding research area, offering advantages such as scalable availability and personalized narration.
arXiv AI
Aug 7
Shaping Human-AI Interactions to Provide Improvement Pathways and Balance Competing Objectives
arXiv:2608. 05710v1 Announce Type: new Abstract: When an AI system is deployed, the individuals who use and or are evaluated by it form beliefs about how the system operates and use those beliefs to strategically present their preferences, behaviors, or attributes.
arXiv AI
Jun 10
Beyond Static Evaluation: Co-Evolutionary Mechanisms for LLM-Driven Strategy Evolution in Adversarial Games
arXiv:2606. 10389v1 Announce Type: new Abstract: Recent advances in LLM-driven code evolution have enabled automated discovery by iteratively generating and improving programs.
arXiv Machine Learning
Jul 1
Partition-Guided Distance Saliency: Bridging Decision and Objective Spaces in Many-Objective Optimization
arXiv:2606. 30836v1 Announce Type: new Abstract: Explainability in Many-Objective Optimization (MaO) is currently hindered by the escalating complexity of the Pareto front, which renders the relationship between high-dimensional decision variables and objective outcomes increasingly opaque.
arXiv AI
Jun 3
Efficient Hyperparameter Optimization for LLM Reinforcement Learning
arXiv:2606. 03073v1 Announce Type: cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is highly sensitive to hyperparameter configurations, making hyperparameter optimization (HPO) essential yet computationally expensive.
arXiv Machine Learning
Jul 10
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
arXiv:2306. 02704v2 Announce Type: replace-cross Abstract: We introduce \emph{Calibrated Stackelberg Games (CSGs)}, a generalization of the standard Stackelberg Games (SGs) framework.