activity
20242026
most citedUnderstanding Risk and Dependency in AI Chatbot Use from User Discourse

2 citations · 6 across the 13 of their papers we have counts for

collaborators
Showing 2026Show all

8 papers · 1 filter

cs.AI2026

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…

cs.AI2026

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…

cs.AI2026

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…

cs.CL2026

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…

cs.CR2026

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…

cs.LG2026

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…

cs.CL2026

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…

cs.CL2026★ 2 cited

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…