Decision-making is a complex process requiring diverse abilities, making it an excellent
framework for evaluating Large Language Models (LLMs). Researchers have examined …

This paper presents a comprehensive survey of the current status and opportunities for
Large Language Models (LLMs) in strategic reasoning, a sophisticated form of reasoning …

Recent advancements in Large Language Models (LLMs) showcase advanced reasoning,
yet NLP evaluations often depend on static benchmarks. Evaluating this necessitates …

With the continuous advancement of network technology, various emerging complex
networking optimization problems have created a wide range of applications utilizing game …

Unlike perfect information games, where all elements are known to every player, imperfect
information games emulate the real-world complexities of decision-making under uncertain …

As AI systems pervade human life, ensuring that large language models (LLMs) make safe
decisions remains a significant challenge. We introduce the Governance of the Commons …

Large Language Models (LLMs) show promising results in language generation and
instruction following but frequently" hallucinate", making their outputs less reliable. Despite …

Current logical reasoning evaluations of Large Language Models (LLMs) primarily focus on
single-turn and static environments, such as arithmetic problems. The crucial problem of …

The behavior of Large Language Models (LLMs) as artificial social agents is largely
unexplored, and we still lack extensive evidence of how these agents react to simple social …

The latest breakthroughs in Large Language Models (LLMs), eg., ChatDev, have catalyzed
profound transformations, particularly through multi-agent collaboration for software …