41 citations · 114 across the 12 of their papers we have counts for
13 papers
Tlow: Flow-based Item Tokenizer for Recommendation
Nian Li, Chonggang Song, Jingtao Ding +3
Item tokenizer encodes semantic embeddings into token IDs to replace the randomly assigned item IDs used in traditional recommendation models, fundamentally addressing the problems…
Exploring Large Language Model Agents for Piloting Social Experiments
Jinghua Piao, Yuwei Yan, Nian Li +2
Computational social experiments, which typically employ agent-based modeling to create testbeds for piloting social experiments, not only provide a computational solution to the m…
A Large-scale Dataset with Behavior, Attributes, and Content of Mobile Short-video Platform
Yu Shang, Chen Gao, Nian Li +1
Short-video platforms show an increasing impact on people's daily lives nowadays, with billions of active users spending plenty of time each day. The interactions between users and…
AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society
Jinghua Piao, Yuwei Yan, Jun Zhang +13
Understanding human behavior and society is a central focus in social sciences, with the rise of generative social science marking a significant paradigmatic shift. By leveraging b…
Modeling User Fatigue for Sequential Recommendation
Nian Li, Xin Ban, Cheng Ling +6
Recommender systems filter out information that meets user interests. However, users may be tired of the recommendations that are too similar to the content they have been exposed…
Uncovering the Deep Filter Bubble: Narrow Exposure in Short-Video Recommendation
Nicholas Sukiennik, Chen Gao, Nian Li
Filter bubbles have been studied extensively within the context of online content platforms due to their potential to cause undesirable outcomes such as user dissatisfaction or pol…
Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network
Lin Chen, Fengli Xu, Nian Li +4
Heterogeneous information networks (HIN) have gained increasing popularity in recent years for capturing complex relations between diverse types of nodes. Meta-structures are propo…
Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives
Chen Gao, Xiaochong Lan, Nian Li +5
Agent-based modeling and simulation has evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. In…
EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities
Nian Li, Chen Gao, Mingyu Li +2
The advent of artificial intelligence has led to a growing emphasis on data-driven modeling in macroeconomics, with agent-based modeling (ABM) emerging as a prominent bottom-up sim…
Alleviating Video-Length Effect for Micro-video Recommendation
Yuhan Quan, Jingtao Ding, Chen Gao +4
Micro-videos platforms such as TikTok are extremely popular nowadays. One important feature is that users no longer select interested videos from a set, instead they either watch t…
Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System
Yunzhu Pan, Nian Li, Chen Gao +5
Short-video recommendation is one of the most important recommendation applications in today's industrial information systems. Compared with other recommendation tasks, the enormou…
Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks
Zirui Zhu, Chen Gao, Xu Chen +3
Incorporating social relations into the recommendation system, i.e. social recommendation, has been widely studied in academic and industrial communities. While many promising resu…
A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions
Chen Gao, Yu Zheng, Nian Li +8
Recommender system is one of the most important information services on today's Internet. Recently, graph neural networks have become the new state-of-the-art approach to recommend…