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researcher

Y. Lai

17 papers hereh-index 6131 citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author11

Across the 17 of 17 papers where every author was matched, so the position is known.

fields
  • cs.LG8
  • cs.CR7
  • cs.AI1
  • cs.IR1
same name
  • Y. Lai — 244 papers
  • Y. Lai — 145 papers, h 18
  • Y. Lai — 109 papers, h 72
  • Y. Lai — 65 papers, h 47
  • Y. Lai — 48 papers, h 26
  • Y. Lai — 22 papers, h 95

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212026
most citedBinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection

8 citations · 11 across the 17 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024★ 1 cited

Defense-as-a-Service: Black-box Shielding against Backdoored Graph Models

Xiao Yang, Kai Zhou, Yuni Lai +1

With the trend of large graph learning models, business owners tend to employ a model provided by a third party to deliver business services to users. However, these models might b…

cs.CR2024

Collective Certified Robustness against Graph Injection Attacks

Yuni Lai, Bailin Pan, Kaihuang Chen +2

We investigate certified robustness for GNNs under graph injection attacks. Existing research only provides sample-wise certificates by verifying each node independently, leading t…

cs.LG2024★ 1 cited

Adversarial Robustness of Link Sign Prediction in Signed Graphs

Jialong Zhou, Xing Ai, Yuni Lai +7

Signed graphs serve as fundamental data structures for representing positive and negative relationships in social networks, with signed graph neural networks (SGNNs) emerging as th…

cs.LG2024

Towards Robust Graph Structural Learning Beyond Homophily via Preserving Neighbor Similarity

Yulin Zhu, Yuni Lai, Xing Ai +7

Despite the tremendous success of graph-based learning systems in handling structural data, it has been widely investigated that they are fragile to adversarial attacks on homophil…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.