13 citations · 55 across the 24 of their papers we have counts for
21 papers
Preference Data Selection for Mitigating the Alignment Tax in Large Language Models
Minsu Kim, Jianxun Lian, Xing Xie +1
Aligning large language models to human preferences is crucial for real-world deployment but frequently incurs an alignment tax, leading to the catastrophic forgetting of pre-train…
To Think or Not To Think, That is The Question for Large Reasoning Models in Theory of Mind Tasks
Nanxu Gong, Haotian Li, Sixun Dong +3
Theory of Mind (ToM) assesses whether models can infer hidden mental states such as beliefs, desires, and intentions, which is essential for natural social interaction. Although re…
HumanLLM: Towards Personalized Understanding and Simulation of Human Nature
Yuxuan Lei, Tianfu Wang, Jianxun Lian +3
Motivated by the remarkable progress of large language models (LLMs) in objective tasks like mathematics and coding, there is growing interest in their potential to simulate human…
Why not Collaborative Filtering in Dual View? Bridging Sparse and Dense Models
Hanze Guo, Jianxun Lian, Xiao Zhou
Collaborative Filtering (CF) remains the cornerstone of modern recommender systems, with dense embedding--based methods dominating current practice. However, these approaches suffe…
BPL: Bias-adaptive Preference Distillation Learning for Recommender System
SeongKu Kang, Jianxun Lian, Dongha Lee +6
Recommender systems suffer from biases that cause the collected feedback to incompletely reveal user preference. While debiasing learning has been extensively studied, they mostly…
Population-Aligned Persona Generation for LLM-based Social Simulation
Zhengyu Hu, Jianxun Lian, Zheyuan Xiao +7
Recent advances in large language models (LLMs) have enabled human-like social simulations at unprecedented scale and fidelity, offering new opportunities for computational social…