17 papers
Seeing Time: Benchmarking Chronological Reasoning and Shortcut Biases in Vision-Language Models
Haoyu Zhou, Qing Qing, Caichong Li +6
Recent advancements in Vision-Language Models (VLMs) have significantly enhanced their ability to interpret complex visual semantics, yet their capacity for chronological reasoning…
Benchmarking Fairness in Spiking Neural Networks: Data Bias, Spurious Features, and Hardware Effects
Hudi He, Fukun Wang, Zhe Wang +7
Evaluating fairness in Spiking Neural Networks (SNNs) demands rigorous benchmarks that reflect real-world complexities, yet existing assessments remain limited by superficial datas…
Learning Multi-Relational Graph Representations for DNA Methylation-Based Biological Age Estimation
Qing Qing, Xikun Zhang, Zhongyuan Zhang +7
Aging clocks aim to estimate biological age, a measure of physiological state distinct from chronological age, from observable biomarkers, and are widely used for health assessment…
GAD in the Wild: Benchmarking Graph Anomaly Detection under Realistic Deployment Challenges
Jingjing Zhou, Shiyu Huang, Qing Qing +7
Graph Anomaly Detection (GAD) is a critical task in graph machine learning with vital applications in financial fraud detection and social platform governance. However, existing GA…
The Missing Adapter Layer for Research Computing
Bowen Li, Jiazhu Xie, Chelsea Wang +3
Higher Degree by Research (HDR) candidates increasingly depend on cloud-provisioned virtual machines and local GPU hardware for their computational experiments, yet a persistent an…
FairGC: Fairness-aware Graph Condensation
Yihan Gao, Chenxi Huang, Wen Shi +5
Graph condensation (GC) has become a vital strategy for scaling Graph Neural Networks by compressing massive datasets into small, synthetic node sets. While current GC methods effe…