Demo Data from SIGIR 2026 / reviewers in the wild / expert
Shenping Xiong
dblp:369/9336
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2026
0009-0006-1706-0511ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Graph learning · 50% Representation and self-supervised learning · 50% | |
| Network and information security
1 paper |
Privacy and data protection · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Graph learning › graph neural network › attention-based graph neural network
graph attention network |
1.0 | 1 | 2026 | TGNN: Enhancing Pixel Tracking Detection via LLM-driven Annotation and GAT-powered Structural Representation · WWW 2026 |
Machine learning › Representation and self-supervised learning
structured representation |
1.0 | 1 | 2026 | TGNN: Enhancing Pixel Tracking Detection via LLM-driven Annotation and GAT-powered Structural Representation · WWW 2026 |
Privacy and data protection
web tracking |
1.0 | 1 | 2026 | TGNN: Enhancing Pixel Tracking Detection via LLM-driven Annotation and GAT-powered Structural Representation · WWW 2026 |
Methods — techniques the papers use, named apart from their topics
large language model · 2.0graph attention network · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | TGNN: Enhancing Pixel Tracking Detection via LLM-driven Annotation and GAT-powered Structural RepresentationabstractWeb tracking is increasingly pervasive, raising serious concerns about user privacy and security. Among existing techniques, pixel tracking is particularly stealthy and cost-effective, embedding invisible images that exfiltrate user activities to third-party servers. Current defenses, including filter list blocking and conventional machine learning, often fail to capture the cross-site associations that enable pixel tracking to evade detection. Shenping Xiong, Xutong Wang, Ze Jin, Xinyu Liu 0019, Haoqiang Wang, Ru Tan, Qixu Liu |
WWW | 1 |
| 2025 | MTAD-Kanformer: multivariate time-series anomaly detection via kan and transformer
Shenping Xiong |
Appl. Intell. | 3 |
| 2025 | MemFlow-AD: An anomaly detection and localization model based on memory module and normalizing flow
Shenping Xiong, Tijian Cai |
J. Vis. Commun. Image Represent. | 3 |