{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/korgym-a-dynamic-game-platform-for-llm","title":"KORGym: A Dynamic Game Platform for LLM Reasoning Evaluation","arxiv_id":"2505.14552","date":"2025-05-20","proceeding":null,"authors":["Jiajun Shi","Jian Yang","Jiaheng Liu","Xingyuan Bu","Jiangjie Chen","Junting Zhou","Kaijing Ma","Zhoufutu Wen","Bingli Wang","Yancheng He","Liang Song","Hualei Zhu","Shilong Li","Xingjian Wang","Wei zhang","Ruibin Yuan","Yifan Yao","Wenjun Yang","Yunli Wang","Siyuan Fang","Siyu Yuan","Qianyu He","Xiangru Tang","Yingshui Tan","Wangchunshu Zhou","Zhaoxiang Zhang","Zhoujun Li","Wenhao Huang","Ge Zhang"],"abstract":"Recent advancements in large language models (LLMs) underscore the need for more comprehensive evaluation methods to accurately assess their reasoning capabilities. Existing benchmarks are often domain-specific and thus cannot fully capture an LLM's general reasoning potential. To address this limitation, we introduce the Knowledge Orthogonal Reasoning Gymnasium (KORGym), a dynamic evaluation platform inspired by KOR-Bench and Gymnasium. KORGym offers over fifty games in either textual or visual formats and supports interactive, multi-turn assessments with reinforcement learning scenarios. Using KORGym, we conduct extensive experiments on 19 LLMs and 8 VLMs, revealing consistent reasoning patterns within model families and demonstrating the superior performance of closed-source models. Further analysis examines the effects of modality, reasoning strategies, reinforcement learning techniques, and response length on model performance. We expect KORGym to become a valuable resource for advancing LLM reasoning research and developing evaluation methodologies suited to complex, interactive environments.","url_abs":"https://arxiv.org/abs/2505.14552v2","url_pdf":"https://arxiv.org/pdf/2505.14552v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"korgym-a-dynamic-game-platform-for-llm","repo_url":"https://github.com/multimodal-art-projection/korgym","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2505.14552","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}