CA2 integrates call stack information into RL agents for game testing and shows consistent gains over baselines that ignore code signals.
Technical Challenges of Deploying Reinforcement Learning Agents for Game Testing in AAA Games
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2representative citing papers
Proof-of-concept shows fine-tuned small language models achieve adequate quality for real-time game content generation in a scoped RPG loop via retry-until-success and LLM-as-judge evaluation.
citing papers explorer
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CA2: Code-Aware Agent for Automated Game Testing
CA2 integrates call stack information into RL agents for game testing and shows consistent gains over baselines that ignore code signals.
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High-quality generation of dynamic game content via small language models: A proof of concept
Proof-of-concept shows fine-tuned small language models achieve adequate quality for real-time game content generation in a scoped RPG loop via retry-until-success and LLM-as-judge evaluation.