activity
20232026
most citedSoMeLVLM: A Large Vision Language Model for Social Media Processing

5 citations · 14 across the 24 of their papers we have counts for

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10 papers · 1 filter

cs.CY2026

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…

cs.LG2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…