2 citations · 6 across the 13 of their papers we have counts for
15 papers
Gradient-Aligned Pair Selection for Personalized Preference Optimization
Ruoming Jin, Xinyu Li, Hao Zhou +6
Personalizing large language models (LLMs) requires aligning generation behavior with user-specific preferences rather than aggregate quality. While Direct Preference Optimization…
Aplaud: Adaptive Personalized Low-Rank Decomposition for User-Specific LLM
Xinyu Li, Ruoming Jin, Jianfeng Zhu +2
In this paper, we study the problem of personalized survey response prediction using fine-tuned large language models (LLMs). This task poses unique challenges: limited per-user tr…
PLUME: Parameter-Efficient Personalization of Large Language Models via Low-Rank User Modulation in Shared Subspaces
Xinyu Li, Hao Zhou, Jianfeng Zhu +4
Personalizing large language models (LLMs) is essential for delivering AI assistance that aligns with individual users' styles, intents, and preferences. While per-user fine-tuning…
When Symptoms Are Not Enough: Evidence-Weighting Patterns in Large Language Model Psychiatric Screening
Jianfeng Zhu, Megan Korhummel, Ruoming Jin +1
As demand for mental health care outpaces clinician-delivered assessment, scalable screening tools are increasingly needed. Large language models (LLMs) may identify psychiatric ri…
Robust LLM Watermarking with Minimal Semantic Distortion for IP Protection
Kieu Dang, Phung Lai, NhatHai Phan +2
Proprietary large language models (LLMs) face risks of intellectual property (IP) violation, as adversaries can replicate an LLM by collecting input-output pairs to train a surroga…
Generalizing Linear Autoencoder Recommenders with Decoupled Expected Quadratic Loss
Ruixin Guo, Xinyu Li, Hao Zhou +2
Linear autoencoders (LAEs) have gained increasing popularity in recommender systems due to their simplicity and strong empirical performance. Most LAE models, including the Emphasi…
What Do AI Agents Talk About? Discourse and Architectural Constraints in the First AI-Only Social Network
Taksch Dube, Jianfeng Zhu, NHatHai Phan +1
Moltbook is the first large-scale social network built for autonomous AI agent-to-agent interaction. Early studies on Moltbook have interpreted its agent discourse as evidence of p…
Understanding Risk and Dependency in AI Chatbot Use from User Discourse
Jianfeng Zhu, Karin G. Coifman, Ruoming Jin
Generative AI systems are increasingly embedded in everyday life, yet empirical understanding of how psychological risk associated with AI use emerges, is experienced, and is regul…
AI-Powered Early Diagnosis of Mental Health Disorders from Real-World Clinical Conversations
Jianfeng Zhu, Julina Maharjan, Xinyu Li +2
Mental health disorders remain among the leading cause of disability worldwide, yet conditions such as depression, anxiety, and Post-Traumatic Stress Disorder (PTSD) are frequently…
Evaluating LLM Alignment on Personality Inference from Real-World Interview Data
Jianfeng Zhu, Julina Maharjan, Xinyu Li +2
Large Language Models (LLMs) are increasingly deployed in roles requiring nuanced psychological understanding, such as emotional support agents, counselors, and decision-making ass…
Can LLMs Infer Personality from Real World Conversations?
Jianfeng Zhu, Ruoming Jin, Karin G. Coifman
Large Language Models (LLMs) such as OpenAI's GPT-4 and Meta's LLaMA offer a promising approach for scalable personality assessment from open-ended language. However, inferring per…
Can Large Language Models Understand Intermediate Representations in Compilers?
Hailong Jiang, Jianfeng Zhu, Yao Wan +4
Intermediate Representations (IRs) play a critical role in compiler design and program analysis, yet their comprehension by Large Language Models (LLMs) remains underexplored. In t…
Investigating Large Language Models in Inferring Personality Traits from User Conversations
Jianfeng Zhu, Ruoming Jin, Karin G. Coifman
Large Language Models (LLMs) are demonstrating remarkable human like capabilities across diverse domains, including psychological assessment. This study evaluates whether LLMs, spe…
Emotions, Context, and Substance Use in Adolescents: A Large Language Model Analysis of Reddit Posts
Jianfeng Zhu, Hailong Jiang, Yulan Wang +3
Early substance use during adolescence increases the risk of later substance use disorders and mental health problems, yet the emotional and contextual factors driving these behavi…
Federated Joint Learning of Robot Networks in Stroke Rehabilitation
Xinyu Jiang, Yibei Guo, Mengsha Hu +4
Advanced by rich perception and precise execution, robots possess immense potential to provide professional and customized rehabilitation exercises for patients with mobility impai…