1.6k citations · 1.6k across the 13 of their papers we have counts for
15 papers
SCBO: Semantically Coherent Batching and Ordering for LLM-Based Social Surveys
Yuanzi Li, Lingjie Wang, Zihang Tian +2
Large Language Models (LLMs) offer a scalable way to simulate survey respondents using demographic profiles and observed reference responses. However, the conventional approach of…
Adaptive Resource Allocation for Effective and Efficient LLM Social Survey Simulation
Yuanzi Li, Xueyang Feng, Junhao Wang +2
Large Language Models (LLMs) enable scalable social survey simulation, yet existing pipelines typically use the same strong general-purpose model and a fixed, often large, responde…
Understanding Reliability in LLM-based Human Behavior Simulation
Pei Wang, Lei Wang, Yuanzi Li +1
Large language models (LLMs) are increasingly used to simulate human survey responses and behavioral reactions, yet unreliable simulations can mislead social science conclusions. H…
Analyzing and Correcting Benevolence Bias in Large Language Models
Yuanzi Li, Junhao Wang, Minghui Liu +9
Large language models (LLMs) are increasingly used as stand-ins for human respondents, from opinion polls and simulated survey participants to agent-based social simulations. These…
Benchmarking LLMs for Community Governance Simulation with Life-history Narratives
Xu Chen, Yuanzi Li, Lei Wang +6
Effective community governance hinges on understanding what specific residents think and need. Recent work has used large language models (LLMs) to simulate human respondents, offe…
Divergence Meets Consensus: A Multi-Source Negative Sampling Framework for Sequential Recommendation
Yuanzi Li, Lingjie Wang, Jingyu Zhao +4
Negative sampling is significant for training sequential recommendation models under implicit feedback. The predominant strategy, self-guided hard negative sampling, selects negati…
LLM Agents as Social Scientists: A Human-AI Collaborative Platform for Social Science Automation
Lei Wang, Yuanzi Li, Jinchao Wu +4
Traditional social science research often requires designing complex experiments across vast methodological spaces and depends on real human participants, making it labor-intensive…
YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models
Lei Wang, Heyang Gao, Xiaohe Bo +2
Leveraging large language model (LLM) based agents to simulate human social behaviors has recently gained significant attention. In this paper, we introduce a novel social simulato…
Explainable Recommendation with Simulated Human Feedback
Jiakai Tang, Jingsen Zhang, Zihang Tian +3
Recent advancements in explainable recommendation have greatly bolstered user experience by elucidating the decision-making rationale. However, the existing methods actually fail t…
Improving Retrospective Language Agents via Joint Policy Gradient Optimization
Xueyang Feng, Bo Lan, Quanyu Dai +5
In recent research advancements within the community, large language models (LLMs) have sparked great interest in creating autonomous agents. However, current prompt-based agents o…
Investigating and Extending Homans' Social Exchange Theory with Large Language Model based Agents
Lei Wang, Zheqing Zhang, Xu Chen
Homans' Social Exchange Theory (SET) is widely recognized as a basic framework for understanding the formation and emergence of human civilizations and social structures. In social…
GenSim: A General Social Simulation Platform with Large Language Model based Agents
Jiakai Tang, Heyang Gao, Xuchen Pan +11
With the rapid advancement of large language models (LLMs), recent years have witnessed many promising studies on leveraging LLM-based agents to simulate human social behavior. Whi…
A Survey on Large Language Model based Autonomous Agents
Lei Wang, Chen Ma, Xueyang Feng +10
Autonomous agents have long been a prominent research focus in both academic and industry communities. Previous research in this field often focuses on training agents with limited…
User Behavior Simulation with Large Language Model based Agents
Lei Wang, Jingsen Zhang, Hao Yang +11
Simulating high quality user behavior data has always been a fundamental problem in human-centered applications, where the major difficulty originates from the intricate mechanism…
Recommendation with User Active Disclosing Willingness
Lei Wang, Xu Chen, Quanyu Dai +1
Recommender system has been deployed in a large amount of real-world applications, profoundly influencing people's daily life and production.Traditional recommender models mostly c…