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researcher

Tong Li

4 papers here

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

author position
  • middle author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • stat.AP2
  • cs.LG1
  • cs.NI1
ORCID 0000-0002-6805-9565
same name
  • Tong Li — 38 papers, h 28
  • Tong Li — 22 papers
  • Tong Li — 6 papers, h 6
  • Tong Li — 3 papers, h 25
  • Tong Li — 3 papers, h 3
  • Tong Li — 3 papers

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

most citedFedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection

30 citations · 30 across the 4 of their papers we have counts for

collaborators

4 papers

cs.NI2025

Pegasus: A Universal Framework for Scalable Deep Learning Inference on the Dataplane

Yinchao Zhang, Su Yao, Yong Feng +9

The paradigm of Intelligent DataPlane (IDP) embeds deep learning (DL) models on the network dataplane to enable intelligent traffic analysis at line-speed. However, the current use…

stat.AP2025

Machine learning bridging battery field data and laboratory data

Yanbin Zhao, Hao Liu, Zhihua Deng +6

Aiming at the dilemma that most laboratory data-driven diagnostic and prognostic methods cannot be applied to field batteries in passenger cars and energy storage systems, this pap…

stat.AP2025

Machine learning accelerates fuel cell life testing

Yanbin Zhao, Hao Liu, Zhihua Deng +6

Accelerated life testing (ALT) can significantly reduce the economic, time, and labor costs of life testing in the process of equipment, device, and material research and developme…

cs.LG2023★ 30 cited

FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection

Yingguang Yang, Renyu Yang, Hao Peng +4

Social bot detection is of paramount importance to the resilience and security of online social platforms. The state-of-the-art detection models are siloed and have largely overloo…

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