2 citations · 5 across the 15 of their papers we have counts for
16 papers
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…
"AI Is Turning Too Human": How Teenagers Experience and Negotiate AI in Everyday Life
Jianfeng Zhu
Generative AI is rapidly entering adolescents' everyday lives during a critical period of cognitive, social and emotional development. Yet its adoption is outpacing evidence on how…
Quantum-Structured World Models (QSWMs) for Predictive Latent Dynamics
Hailong Jiang, Emran Hossain, Feng Yu +3
World models learn latent states that summarize interaction histories, evolve over time, and support prediction, simulation, or planning. Most existing world models represent these…
Can Large Language Models Recover Semantic Optimization Opportunities That Compilers Miss?
Hailong Jiang, Feng Yu, Emran Hossain +4
Optimizing compilers miss profitable transformations when their enabling semantics are absent from the analyzed program representation. We ask whether large language models (LLMs)…
BMOA: Baseline-Mechanism-Outcome Attribution for Compiler-Induced Numerical Deviations
Hailong Jiang, Emran Hossain, Feng Yu +4
Formalizing compiler-aware numerical correctness requires distinguishing what an observed floating-point difference means, what compiler behavior the evidence supports, and what nu…
Characterizing the Temporal, Emotional, and Social Patterns of Adolescent Substance Use Discussions on Reddit
Leran Hong, Lei Jin, Jianfeng Zhu
Adolescence is a critical developmental period marked by heightened emotional sensitivity, social stress, and vulnerability to substance use. However, traditional research methods…
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…
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…