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Jiehang Zeng

Jiehang Zeng has 2 papers in our library, in 2020–2023, most of them on Dependency parsing, Evaluation & benchmarks, English; often with Xiaoqing Zheng, Xuanjing Huang, Cho-Jui Hsieh.

2 papers in our library · 2020–2023

OpenAlex · ORCID · h-index 6 · 10 works · 602 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 92 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6124

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

🎓Fudan UniversityShanghai · China2020–2023 · 7 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution 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 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 3Research subjects and languages the work is about.Dependency parsing · 1 workEnglish · 1 workEvaluation & benchmarks · 1 work

 Works by year

2020s

20231 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Certified Robustness to Text Adversarial Attacks by Randomized [MASK] (2023 · 101 citations)
    Text classifiers, including BERT-based ones, can be fooled by small edits such as synonym swaps or deliberate misspellings.
  2. Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples (2020 · 54 citations)
    The authors ask whether a neural graph parser (the Dozat and Manning biaffine model) can be fooled by an edit that keeps the syntax of the sentence.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Backdoor Attacks on Pre-trained Models by Layerwise Weight Poisoning ↗Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · no summary yetLinyang Li et al.2021 · 141 citations
  2. Certified Robustness to Text Adversarial Attacks by Randomized [MASK]Computational LinguisticsJiehang Zeng, Jianhan Xu, Xiaoqing Zheng, et al.2023 · 101 citations
  3. Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial ExamplesXiaoqing Zheng, Jiehang Zeng, Yi Zhou, et al.English · 54 citations

 Co-authors here

4 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 92 times (of the 149,439 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated

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