Explore the Reasoning Capability of LLMs in the Chess Testbed
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Shu, Ji, Lei, Wang, Renxi, Zhao, Wenxiao, Liu, Haokun, Hou, Yifan, Wu, Ying Nian |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LLM CHESS: Benchmarking Reasoning and Instruction-Following in LLMs through Chess
by: Kolasani, Sai, et al.
Published: (2025)
by: Kolasani, Sai, et al.
Published: (2025)
ChessArena: A Chess Testbed for Evaluating Strategic Reasoning Capabilities of Large Language Models
by: Liu, Jincheng, et al.
Published: (2025)
by: Liu, Jincheng, et al.
Published: (2025)
Are Your LLMs Capable of Stable Reasoning?
by: Liu, Junnan, et al.
Published: (2024)
by: Liu, Junnan, et al.
Published: (2024)
Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data
by: Liu, Xiao, et al.
Published: (2024)
by: Liu, Xiao, et al.
Published: (2024)
oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning
by: Xu, Ruiling, et al.
Published: (2025)
by: Xu, Ruiling, et al.
Published: (2025)
Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks
by: Wu, Zhaofeng, et al.
Published: (2023)
by: Wu, Zhaofeng, et al.
Published: (2023)
Exploring the System 1 Thinking Capability of Large Reasoning Models
by: Zhang, Wenyuan, et al.
Published: (2025)
by: Zhang, Wenyuan, et al.
Published: (2025)
HiBench: Benchmarking LLMs Capability on Hierarchical Structure Reasoning
by: Jiang, Zhuohang, et al.
Published: (2025)
by: Jiang, Zhuohang, et al.
Published: (2025)
CHBench: A Cognitive Hierarchy Benchmark for Evaluating Strategic Reasoning Capability of LLMs
by: Liu, Hongtao, et al.
Published: (2025)
by: Liu, Hongtao, et al.
Published: (2025)
Cooperative Strategic Planning Enhances Reasoning Capabilities in Large Language Models
by: Wang, Danqing, et al.
Published: (2024)
by: Wang, Danqing, et al.
Published: (2024)
CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual Worlds
by: Wang, Lei, et al.
Published: (2024)
by: Wang, Lei, et al.
Published: (2024)
Generalization of RLVR Using Causal Reasoning as a Testbed
by: Lu, Brian, et al.
Published: (2025)
by: Lu, Brian, et al.
Published: (2025)
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs
by: Chen, Junying, et al.
Published: (2024)
by: Chen, Junying, et al.
Published: (2024)
Exploring ChatGPT's Capabilities on Vulnerability Management
by: Liu, Peiyu, et al.
Published: (2023)
by: Liu, Peiyu, et al.
Published: (2023)
Olapa-MCoT: Enhancing the Chinese Mathematical Reasoning Capability of LLMs
by: Zhu, Shaojie, et al.
Published: (2023)
by: Zhu, Shaojie, et al.
Published: (2023)
Exploring the Personality Traits of LLMs through Latent Features Steering
by: Yang, Shu, et al.
Published: (2024)
by: Yang, Shu, et al.
Published: (2024)
Quantization Meets dLLMs: A Systematic Study of Post-training Quantization for Diffusion LLMs
by: Lin, Haokun, et al.
Published: (2025)
by: Lin, Haokun, et al.
Published: (2025)
Chain-of-Defensive-Thought: Structured Reasoning Elicits Robustness in Large Language Models against Reference Corruption
by: Wang, Wenxiao, et al.
Published: (2025)
by: Wang, Wenxiao, et al.
Published: (2025)
Ko-MuSR: A Multistep Soft Reasoning Benchmark for LLMs Capable of Understanding Korean
by: Park, Chanwoo, et al.
Published: (2025)
by: Park, Chanwoo, et al.
Published: (2025)
Improving LLM Reasoning through Interpretable Role-Playing Steering
by: Wang, Anyi, et al.
Published: (2025)
by: Wang, Anyi, et al.
Published: (2025)
KAG-Thinker: Interactive Thinking and Deep Reasoning in LLMs via Knowledge-Augmented Generation
by: Zhang, Dalong, et al.
Published: (2025)
by: Zhang, Dalong, et al.
Published: (2025)
Unlocking Reasoning Capabilities in LLMs via Reinforcement Learning Exploration
by: Deng, Wenhao, et al.
Published: (2025)
by: Deng, Wenhao, et al.
Published: (2025)
Thoughts-as-Planning: Latent World Models for Chain-of-Thoughts Optimization via Reinforcement Planning
by: Liu, Dong, et al.
Published: (2026)
by: Liu, Dong, et al.
Published: (2026)
Don't Take Things Out of Context: Attention Intervention for Enhancing Chain-of-Thought Reasoning in Large Language Models
by: Yan, Shaotian, et al.
Published: (2025)
by: Yan, Shaotian, et al.
Published: (2025)
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
by: DeepSeek-AI, et al.
Published: (2025)
by: DeepSeek-AI, et al.
Published: (2025)
High Accuracy, Less Talk (HALT): Reliable LLMs through Capability-Aligned Finetuning
by: Franzmeyer, Tim, et al.
Published: (2025)
by: Franzmeyer, Tim, et al.
Published: (2025)
Are Smarter LLMs Safer? Exploring Safety-Reasoning Trade-offs in Prompting and Fine-Tuning
by: Li, Ang, et al.
Published: (2025)
by: Li, Ang, et al.
Published: (2025)
Distilling Mathematical Reasoning Capabilities into Small Language Models
by: Zhu, Xunyu, et al.
Published: (2024)
by: Zhu, Xunyu, et al.
Published: (2024)
Concise and Organized Perception Facilitates Reasoning in Large Language Models
by: Liu, Junjie, et al.
Published: (2023)
by: Liu, Junjie, et al.
Published: (2023)
How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs
by: Feng, Guhao, et al.
Published: (2024)
by: Feng, Guhao, et al.
Published: (2024)
Enhancing the General Agent Capabilities of Low-Parameter LLMs through Tuning and Multi-Branch Reasoning
by: Zhou, Qinhao, et al.
Published: (2024)
by: Zhou, Qinhao, et al.
Published: (2024)
CoT-Driven Framework for Short Text Classification: Enhancing and Transferring Capabilities from Large to Smaller Model
by: Wu, Hui, et al.
Published: (2024)
by: Wu, Hui, et al.
Published: (2024)
Compose and Fuse: Revisiting the Foundational Bottlenecks in Multimodal Reasoning
by: Wang, Yucheng, et al.
Published: (2025)
by: Wang, Yucheng, et al.
Published: (2025)
Evaluating LLMs' Divergent Thinking Capabilities for Scientific Idea Generation with Minimal Context
by: Ruan, Kai, et al.
Published: (2024)
by: Ruan, Kai, et al.
Published: (2024)
Complete Chess Games Enable LLM Become A Chess Master
by: Zhang, Yinqi, et al.
Published: (2025)
by: Zhang, Yinqi, et al.
Published: (2025)
Exploring the psychology of LLMs' Moral and Legal Reasoning
by: Almeida, Guilherme F. C. F., et al.
Published: (2023)
by: Almeida, Guilherme F. C. F., et al.
Published: (2023)
Exploiting LLMs' Reasoning Capability to Infer Implicit Concepts in Legal Information Retrieval
by: Nguyen, Hai-Long, et al.
Published: (2024)
by: Nguyen, Hai-Long, et al.
Published: (2024)
CoME: Empowering Channel-of-Mobile-Experts with Informative Hybrid-Capabilities Reasoning
by: Liu, Yuxuan, et al.
Published: (2026)
by: Liu, Yuxuan, et al.
Published: (2026)
Capabilities of GPT-5 on Multimodal Medical Reasoning
by: Wang, Shansong, et al.
Published: (2025)
by: Wang, Shansong, et al.
Published: (2025)
Emergent Hierarchical Reasoning in LLMs through Reinforcement Learning
by: Wang, Haozhe, et al.
Published: (2025)
by: Wang, Haozhe, et al.
Published: (2025)
Similar Items
-
LLM CHESS: Benchmarking Reasoning and Instruction-Following in LLMs through Chess
by: Kolasani, Sai, et al.
Published: (2025) -
ChessArena: A Chess Testbed for Evaluating Strategic Reasoning Capabilities of Large Language Models
by: Liu, Jincheng, et al.
Published: (2025) -
Are Your LLMs Capable of Stable Reasoning?
by: Liu, Junnan, et al.
Published: (2024) -
Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data
by: Liu, Xiao, et al.
Published: (2024) -
oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning
by: Xu, Ruiling, et al.
Published: (2025)