5 papers
You Can't Fool Us: Understanding the Resilience of LLM-driven Agent Communities to Misinformation
Chichen Lin, Yijie Jin, Kangbo Hu +5
Misinformation resilience is a dynamic community process: communities differ not only in whether they initially trust false claims, but also in how they recover through interaction…
RcLLM: Accelerating Generative Recommendation via Beyond-Prefix KV Caching
Zhan Zhao, Yuxin Wang, Amelie Chi Zhou
Large Language Models (LLMs) are transforming recommendation from ranking into a generative task, but industrial deployment remains limited by the high latency of processing long,…
Incentivizing User Data Contributions for LLM Improvement under Withdrawal Rights
Di Feng, Chenhao Zhang, Zhanzhan Zhao
The continued improvement of large language models (LLMs) increasingly depends on eliciting high-quality, user-generated data, yet such data are costly to provide and often withhel…
The Emergence of Social Science of Large Language Models
Xiao Jia, Zhanzhan Zhao
The social science of large language models (LLMs) examines how these systems evoke mind attributions, interact with one another, and transform human activity and institutions. We…
The Emergence of Altruism in Large-Language-Model Agents Society
Haoyang Li, Xiao Jia, Zhanzhan Zhao
Leveraging Large Language Models (LLMs) for social simulation is a frontier in computational social science. Understanding the social logics these agents embody is critical to this…