5 citations · 14 across the 24 of their papers we have counts for
25 papers
Uncovering Salience-Driven Dynamics in Consumer Confidence with Generative Social Simulation
Yixu Huang, Yunlu Yin, Jiayu Lin +6
Consumer confidence is typically modeled as a persistent macroeconomic index, yet its movements arise from households that interpret economic information through heterogeneous cons…
Large Language Models Hack Rewards, and Society
Wei Liu, Xinyi Mou, Hanqi Yan +2
Reinforcement learning (RL) has become a dominant post-training paradigm, enabling large language models (LLMs) to learn from rewards. We observe that societal regulations are stru…
Revising Context, Shifting Simulated Stance: Auditing LLM-Based Stance Simulation in Online Discussions
Xinnong Zhang, Wanting Shan, Hanjia Lyu +2
Large language models are increasingly used to simulate social media users and infer how individuals may respond to online discussions. However, it remains unclear whether these si…
Beyond Isolated Behaviors: Hierarchical User Modeling for LLM Personalization
Liang Wang, Xinyi Mou, Xiaoyou Liu +3
Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse domains, yet personalizing their outputs to individual users remains an open challenge. Existi…
LifeSim: Long-Horizon User Life Simulator for Personalized Assistant Evaluation
Feiyu Duan, Xuanjing Huang, Zhongyu Wei
The rapid advancement of large language models (LLMs) has accelerated progress toward universal AI assistants. However, existing benchmarks for personalized assistants remain misal…
Towards a Science of Collective AI: LLM-based Multi-Agent Systems Need a Transition from Blind Trial-and-Error to Rigorous Science
Jingru Fan, Dewen Liu, Yufan Dang +15
Recent advancements in Large Language Models (LLMs) have greatly extended the capabilities of Multi-Agent Systems (MAS), demonstrating significant effectiveness across a wide range…
CURP: Codebook-based Continuous User Representation for Personalized Generation with LLMs
Liang Wang, Xinyi Mou, Xiaoyou Liu +2
User modeling characterizes individuals through their preferences and behavioral patterns to enable personalized simulation and generation with Large Language Models (LLMs) in cont…
Strong Reasoning Isn't Enough: Evaluating Evidence Elicitation in Interactive Diagnosis
Zhuohan Long, Zhijie Bao, Zhongyu Wei
Interactive medical consultation requires an agent to proactively elicit missing clinical evidence under uncertainty. Yet existing evaluations largely remain static or outcome-cent…
CommunityBench: Benchmarking Community-Level Alignment across Diverse Groups and Tasks
Jiayu Lin, Zhongyu Wei
Large language models (LLMs) alignment ensures model behaviors reflect human value. Existing alignment strategies primarily follow two paths: one assumes a universal value set for…
PersonaDual: Balancing Personalization and Objectivity via Adaptive Reasoning
Xiaoyou Liu, Xinyi Mou, Shengbin Yue +5
As users increasingly expect LLMs to align with their preferences, personalized information becomes valuable. However, personalized information can be a double-edged sword: it can…
VL-Cogito: Progressive Curriculum Reinforcement Learning for Advanced Multimodal Reasoning
Ruifeng Yuan, Chenghao Xiao, Sicong Leng +9
Reinforcement learning has proven its effectiveness in enhancing the reasoning capabilities of large language models. Recent research efforts have progressively extended this parad…
ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset
Yilin Wang, Peixuan Lei, Jie Song +6
Time-series data are critical in diverse applications, such as industrial monitoring, medical diagnostics, and climate research. However, effectively integrating these high-dimensi…
EcoLANG: Efficient and Effective Agent Communication Language Induction for Social Simulation
Xinyi Mou, Chen Qian, Wei Liu +2
Large language models (LLMs) have demonstrated an impressive ability to role-play humans and replicate complex social dynamics. While large-scale social simulations are gaining inc…
SocioVerse: A World Model for Social Simulation Powered by LLM Agents and A Pool of 10 Million Real-World Users
Xinnong Zhang, Jiayu Lin, Xinyi Mou +18
Social simulation is transforming traditional social science research by modeling human behavior through interactions between virtual individuals and their environments. With recen…
Word Form Matters: LLMs' Semantic Reconstruction under Typoglycemia
Chenxi Wang, Tianle Gu, Zhongyu Wei +3
Human readers can efficiently comprehend scrambled words, a phenomenon known as Typoglycemia, primarily by relying on word form; if word form alone is insufficient, they further ut…
Multi-agent KTO: Reinforcing Strategic Interactions of Large Language Model in Language Game
Rong Ye, Yongxin Zhang, Yikai Zhang +3
Achieving Artificial General Intelligence (AGI) requires AI agents that can not only make stratigic decisions but also engage in flexible and meaningful communication. Inspired by…
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…
ElectionSim: Massive Population Election Simulation Powered by Large Language Model Driven Agents
Xinnong Zhang, Jiayu Lin, Libo Sun +10
The massive population election simulation aims to model the preferences of specific groups in particular election scenarios. It has garnered significant attention for its potentia…
AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models
Xiawei Liu, Shiyue Yang, Xinnong Zhang +6
The rise of various social platforms has transformed journalism. The growing demand for news content has led to the increased use of large language models (LLMs) in news production…
Overview of AI-Debater 2023: The Challenges of Argument Generation Tasks
Jiayu Lin, Guanrong Chen, Bojun Jin +26
In this paper we present the results of the AI-Debater 2023 Challenge held by the Chinese Conference on Affect Computing (CCAC 2023), and introduce the related datasets. We organiz…
SoMeLVLM: A Large Vision Language Model for Social Media Processing
Xinnong Zhang, Haoyu Kuang, Xinyi Mou +6
The growth of social media, characterized by its multimodal nature, has led to the emergence of diverse phenomena and challenges, which calls for an effective approach to uniformly…
Unveiling the Truth and Facilitating Change: Towards Agent-based Large-scale Social Movement Simulation
Xinyi Mou, Zhongyu Wei, Xuanjing Huang
Social media has emerged as a cornerstone of social movements, wielding significant influence in driving societal change. Simulating the response of the public and forecasting the…
Human vs. LMMs: Exploring the Discrepancy in Emoji Interpretation and Usage in Digital Communication
Hanjia Lyu, Weihong Qi, Zhongyu Wei +1
Leveraging Large Multimodal Models (LMMs) to simulate human behaviors when processing multimodal information, especially in the context of social media, has garnered immense intere…