7 papers
Mitigating Identity Essentialism in LLM Agents with Longitudinal Life Trajectories
Hexi Wang, Yujia Zhou, Bangde Du +7
Large language models (LLMs) offer a scalable approach to social simulation, but their credibility depends on how agents are constructed. Existing methods can partially reproduce p…
Retrievable Gradients: Continual Post-Training Without Cumulative Weight Drift
Weihang Su, Jiacheng Kang, Jingyan Xu +7
Continual post-training enables models to absorb emerging knowledge after deployment, but repeatedly updating shared parameters can accumulate weight drift, potentially causing cat…
Parametric Social Identity Injection and Diversification in Public Opinion Simulation
Hexi Wang, Yujia Zhou, Bangde Du +2
Large language models (LLMs) have recently been adopted as synthetic agents for public opinion simulation, offering a promising alternative to costly and slow human surveys. Despit…
How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study
Shuqi Zhu, Yi Zhong, Ziyi Ye +4
While AI-generated hallucinations pose considerable risks, the underlying cognitive mechanisms by which humans can successfully recognize or be misled by these hallucinations remai…
TwinVoice: A Multi-dimensional Benchmark Towards Digital Twins via LLM Persona Simulation
Bangde Du, Minghao Guo, Songming He +8
Large Language Models (LLMs) are exhibiting emergent human-like abilities and are increasingly envisioned as the foundation for simulating an individual's communication style, beha…
ValueSim: Generating Backstories to Model Individual Value Systems
Bangde Du, Ziyi Ye, Zhijing Wu +5
As Large Language Models (LLMs) continue to exhibit increasingly human-like capabilities, aligning them with human values has become critically important. Contemporary advanced tec…