1 citations · 1 across the 5 of their papers we have counts for
5 papers
Mean Mode Screaming: Mean--Variance Split Residuals for 1000-Layer Diffusion Transformers
Pengqi Lu
Scaling Diffusion Transformers (DiTs) to hundreds of layers introduces a structural vulnerability: networks can enter a silent, mean-dominated collapse state that homogenizes token…
TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG
Pengqian Lu, Jie Lu, Anjin Liu +1
Detecting hallucinations in Retrieval-Augmented Generation remains a challenge. Prior approaches attribute hallucinations to a binary conflict between internal knowledge stored in…
Autonomous Concept Drift Threshold Determination
Pengqian Lu, Jie Lu, Anjin Liu +2
Existing drift detection methods focus on designing sensitive test statistics. They treat the detection threshold as a fixed hyperparameter, set once to balance false alarms and la…
Early Concept Drift Detection via Prediction Uncertainty
Pengqian Lu, Jie Lu, Anjin Liu +1
Concept drift, characterized by unpredictable changes in data distribution over time, poses significant challenges to machine learning models in streaming data scenarios. Although…
Regularly Truncated M-estimators for Learning with Noisy Labels
Xiaobo Xia, Pengqian Lu, Chen Gong +3
The sample selection approach is very popular in learning with noisy labels. As deep networks learn pattern first, prior methods built on sample selection share a similar training…