activity
20172024
most citedEncircling exceptional points in a Riemann sphere for efficient asymmetric polarization-locked devices

102 citations · 138 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2024★ 3 cited

Anomaly Detection of Tabular Data Using LLMs

Aodong Li, Yunhan Zhao, Chen Qiu +4

Large language models (LLMs) have shown their potential in long-context understanding and mathematical reasoning. In this paper, we study the problem of using LLMs to detect tabula…

physics.optics2024

Multi-state Chiral Switching Through Adiabaticity Control in Encircling Exceptional Points

Aodong Li, Jian Wang, Andrea Alù +1

Dynamic encircling of exceptional points has attracted significant interest in recent years, as it can facilitate chiral transmission selectivity due to a nontrivial eigenstate evo…

cs.LG2023★ 1 cited

Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data

Clement Fung, Chen Qiu, Aodong Li +1

Anomaly detection is the task of identifying abnormal samples in large unlabeled datasets. While the advent of foundation models has produced powerful zero-shot anomaly detection m…

cs.LG2023★ 9 cited

Zero-Shot Anomaly Detection via Batch Normalization

Aodong Li, Chen Qiu, Marius Kloft +3

Anomaly detection (AD) plays a crucial role in many safety-critical application domains. The challenge of adapting an anomaly detector to drift in the normal data distribution, esp…

cs.LG2023★ 1 cited

Deep Anomaly Detection under Labeling Budget Constraints

Aodong Li, Chen Qiu, Marius Kloft +3

Selecting informative data points for expert feedback can significantly improve the performance of anomaly detection (AD) in various contexts, such as medical diagnostics or fraud…

cs.LG2022★ 17 cited

Latent Outlier Exposure for Anomaly Detection with Contaminated Data

Chen Qiu, Aodong Li, Marius Kloft +2

Anomaly detection aims at identifying data points that show systematic deviations from the majority of data in an unlabeled dataset. A common assumption is that clean training data…