arXiv:2606. 14715v1 Announce Type: cross Abstract: LLM agents are increasingly used to simulate real world interactions, but it remains unclear whether simulated behaviors preserve the content patterns and interaction dynamics of real human behaviors.
By Yaoning Yu, Ye Yu, Haojing Luo, Haohan Wang
arXiv:2608. 09790v1 Announce Type: new Abstract: Online credit card discussions provide a natural setting for studying how consumers communicate about financial products.
By Yaoning Yu, Kai-Min Chang, Ye Yu, Yi-Chia Wang, Haojing Luo, Haohan Wang
arXiv:2610.20360v1 Announce Type: new
Abstract: Gossip, defined as evaluative talk about absent third parties, is widely seen as a uniquely human social practice. This study examines whether comparab...
By Yong-Hui Hua, Chih-Han Lin, Shu-Kai Hsieh
arXiv:2606. 06027v1 Announce Type: cross Abstract: Community-conditioned language model adaptation requires choices about data collection, community definition, and evaluation that are currently made independently in each study, making it hard to compare assumptions or reuse artifacts.
By Amirhossein Ghaffari, Ali Goodarzi, Huong Nguyen, Simo Hosio, Lauri Lov\'en, Ekaterina Gilman
arXiv:2610.14570v1 Announce Type: new
Abstract: Large language models (LLMs) support social simulation, but faithfully reproducing real users requires grounding both structured platform decisions and...
By Wenji Zhang, Xilong Cheng, Yunxiao Qin, Mai Tu, Tongye Zhu, Yuhao Zhou, JingBo Ji, Yuting Tan, Duoyin Li, Hongjiang Xiao, Yuan Zhang
arXiv:2601. 19921v2 Announce Type: replace-cross Abstract: Multi-agent debate (MAD) is widely used to improve large language model (LLM) performance through test-time scaling, yet recent work shows that vanilla MAD often underperforms simple majority vote despite higher computational cost.
By Xiaochen Zhu, Caiqi Zhang, Yizhou Chi, Tom Stafford, Nigel Collier, Andreas Vlachos