4 papers
Effort as Ceiling, Not Dial: Reasoning Budget Does Not Modulate Cognitive Cost Alignment Between Humans and Large Reasoning Models
Yueqing Hu, Tianhong Wang
Large Reasoning Models (LRMs) generate chain-of-thought traces whose length tracks human reaction times across cognitive tasks, but recent debate questions whether this alignment r…
Hán DÄn Xué Bù (Mimicry) or QÄ«ng ChÅ« Yú Lán (Mastery)? A Cognitive Perspective on Reasoning Distillation in Large Language Models
Yueqing Hu, Xinyang Peng, Shuting Peng +2
Recent Large Reasoning Models trained via reinforcement learning exhibit a "natural" alignment with human cognitive costs. However, we show that the prevailing paradigm of reasonin…
Social Catalysts, Not Moral Agents: The Illusion of Alignment in LLM Societies
Yueqing Hu, Yixuan Jiang, Zehua Jiang +2
The rapid evolution of Large Language Models (LLMs) has led to the emergence of Multi-Agent Systems where collective cooperation is often threatened by the "Tragedy of the Commons.…
Beyond Instrumental and Substitutive Paradigms: Introducing Machine Culture as an Emergent Phenomenon in Large Language Models
Yueqing Hu, Xinyang Peng, Yukun Zhao +3
Recent scholarship typically characterizes Large Language Models (LLMs) through either an \textit{Instrumental Paradigm} (viewing models as reflections of their developers' culture…