output
20122025
most citedApplications of Deep Learning Techniques for Automated Multiple Sclerosis Detection Using Magnetic Resonance Imaging: A Review

187 citations

22 papers

cs.SE2025

MINES: Explainable Anomaly Detection through Web API Invariant Inference

Wenjie Zhang, Yun Lin, Chun Fung Amos Kwok +5

Detecting the anomalies of web applications, important infrastructures for running modern companies and governments, is crucial for providing reliable web services. Many modern web…

cs.CV2025

Eyes on Target: Gaze-Aware Object Detection in Egocentric Video

Vishakha Lall, Yisi Liu

Human gaze offers rich supervisory signals for understanding visual attention in complex visual environments. In this paper, we propose Eyes on Target, a novel depth-aware and gaze…

eess.AS2025★ 1 cited

Dynamic Stress Detection: A Study of Temporal Progression Modelling of Stress in Speech

Vishakha Lall, Yisi Liu

Detecting psychological stress from speech is critical in high-pressure settings. While prior work has leveraged acoustic features for stress detection, most treat stress as a stat…

cs.AI2025

Prompt-and-Check: Using Large Language Models to Evaluate Communication Protocol Compliance in Simulation-Based Training

Vishakha Lall, Yisi Liu

Accurate evaluation of procedural communication compliance is essential in simulation-based training, particularly in safety-critical domains where adherence to compliance checklis…

cs.CV2025

Enhancing Egocentric Object Detection in Static Environments using Graph-based Spatial Anomaly Detection and Correction

Vishakha Lall, Yisi Liu

In many real-world applications involving static environments, the spatial layout of objects remains consistent across instances. However, state-of-the-art object detection models…

cs.CR2025

Out of Distribution, Out of Luck: How Well Can LLMs Trained on Vulnerability Datasets Detect Top 25 CWE Weaknesses?

Yikun Li, Ngoc Tan Bui, Ting Zhang +16

Automated vulnerability detection research has made substantial progress, yet its real-world impact remains limited. Prior work found that current vulnerability datasets suffer fro…