4 papers
HardcoreLogic: Challenging Large Reasoning Models with Long-tail Logic Puzzle Games
Jingcong Liang, Shijun Wan, Xuehai Wu +5
Large Reasoning Models (LRMs) have demonstrated impressive performance on complex tasks, including logical puzzle games that require deriving solutions satisfying all constraints.…
Not All Models Suit Expert Offloading: On Local Routing Consistency of Mixture-of-Expert Models
Jingcong Liang, Siyuan Wang, Miren Tian +3
Mixture-of-Experts (MoE) enables efficient scaling of large language models (LLMs) with sparsely activated experts during inference. To effectively deploy large MoE models on memor…
From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents
Xinyi Mou, Xuanwen Ding, Qi He +8
Traditional sociological research often relies on human participation, which, though effective, is expensive, challenging to scale, and with ethical concerns. Recent advancements i…
AgentSense: Benchmarking Social Intelligence of Language Agents through Interactive Scenarios
Xinyi Mou, Jingcong Liang, Jiayu Lin +8
Large language models (LLMs) are increasingly leveraged to empower autonomous agents to simulate human beings in various fields of behavioral research. However, evaluating their ca…