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Wenkai Yang

Wenkai Yang has 2 papers in our library, in 2021; often with Xu Sun, Jie Zhou, Lei Li.

2 papers in our library · 2021

OpenAlex · ORCID · h-index 15 · 65 works · 820 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 206 times in our library · ⭐ Paper Stars ranking: #4442

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Renmin University of ChinaBeijing · China2023–2026 · 9 paperscurrent🎓ShanghaiTech UniversityShanghai · China2025–2026 · 5 paperscurrent🎓Australian National UniversityCanberra · Australia2025–2026 · 4 paperscurrent🎓Shandong Youth University of Political ScienceJinan · China2021–2026 · 2 paperscurrent🎓China University of Mining and TechnologyXuzhou · China2026 · 1 papercurrent🎓Peking UniversityBeijing · China2021–2025 · 10 papers🎓Taiyuan University of TechnologyTaiyuan · China2019–2025 · 10 papers🎓Tianjin UniversityTianjin · China2015–2020 · 5 papers🎓Shanxi UniversityTaiyuan · China2021–2022 · 3 papers🎓Waseda UniversityTokyo · Japan2023–2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 work

 Works by year

2020s

20212 papersWenkai Yang's papers of 2021

 Papers

The most cited first (OpenAlex and our library).

  1. Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models (2021 · 134 citations)
    Backdoor attacks make an NLP classifier behave normally on ordinary inputs but output an attacker-chosen class whenever a rare trigger word appears.
  2. RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models (2021 · 112 citations)
    The paper addresses run-time protection of NLP classifiers obtained from untrusted third parties, which may contain backdoors: hidden triggers that force a chosen target label.

 Co-authors here

7 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 206 times (of the 141,840 papers whose bibliographies we read); 3 citing papers with a page here →.

Updated

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