most citedAI-Powered Early Diagnosis of Mental Health Disorders from Real-World Clinical Conversations

1 citations · 1 across the 6 of their papers we have counts for

collaborators

8 papers

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.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.LG2026

Interpretable Maximum Margin Deep Anomaly Detection

Zhiji Yang, Mei Huang, Xinyu Li +3

Anomaly detection is a crucial machine-learning task with wide-ranging applications. Deep Support Vector Data Description (Deep SVDD) is a prominent deep one-class method, but it i…

stat.ML2025

PAC-Bayes Bounds for Multivariate Linear Regression and Linear Autoencoders

Ruixin Guo, Ruoming Jin, Xinyu Li +1

Linear Autoencoders (LAEs) have shown strong performance in state-of-the-art recommender systems. However, this success remains largely empirical, with limited theoretical understa…

cs.CL2025★ 1 cited

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…

cs.CL2025

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…