3 papers
stat.ML2026
PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Models
Qi Qin, Erbo Li, Ting Wei +4
In high-dimensional tabular learning, feature screening provides a lightweight, model-agnostic way to remove irrelevant features before model fitting. However, scoring raw values d…
cs.AI2025
The Achilles' Heel of LLMs: How Altering a Handful of Neurons Can Cripple Language Abilities
Zixuan Qin, Qingchen Yu, Kunlin Lyu +2
Large Language Models (LLMs) have become foundational tools in natural language processing, powering a wide range of applications and research. Many studies have shown that LLMs sh…
cs.LG2024
Enhancing Data Quality through Self-learning on Imbalanced Financial Risk Data
Xu Sun, Zixuan Qin, Shun Zhang +2
In the financial risk domain, particularly in credit default prediction and fraud detection, accurate identification of high-risk class instances is paramount, as their occurrence…