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Zenglin Xu

Zenglin Xu has 3 papers in our library, in 2021–2026, most of them on Part-of-speech tagging, Language models & pretraining, Evaluation & benchmarks; often with Deqing Zou, Hai-Tao Zheng, Irwin King.

3 papers in our library · 2021–2026

OpenAlex · ORCID · Wikidata · h-index 53 · 371 works · 11,241 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 32 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #10903

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

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 8 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.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. Position: LLMs Can be Good Tutors in English Education (2025 · 9 citations)
    This is a position paper. It runs no experiments and introduces no dataset. The authors argue that current LLM uses in English teaching mostly reuse standard NLP task framings and ignore educational methodology. They contend that LLMs can work as tutors that support human teachers rather than replace them. They…
  2. SiPOS: A Benchmark Dataset for Sindhi Part-of-Speech Tagging (2021 · 3 citations)
    Sindhi is a morphologically rich language but has very few resources. Until now it has had no open and sufficiently large annotated corpus for part-of-speech (POS) tagging: earlier datasets are either too small or not publicly available. The authors created SiPOS, a gold-standard dataset built from Sindhi news texts…
  3. CoTEvol: Self-Evolving Chain-of-Thoughts for Data Synthesis in Mathematical Reasoning (2026)
    Training LLMs for math reasoning depends on high-quality Chain-of-Thought (CoT) data, which is expensive to annotate.

All works

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

  1. Large-Scale Multi-View Subspace Clustering in Linear Time ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetZhao Kang et al.2020 · 539 citations
  2. FedPETuning: When Federated Learning Meets the Parameter-Efficient Tuning Methods of Pre-trained Language Models ↗Findings of the Association for Computational Linguistics: ACL 2023 · no summary yetZhuo Zhang et al.2023 · 108 citations
  3. Non-monotonic feature selection ↗International Conference on Machine Learning · no summary yetZenglin Xu et al.2009 · 65 citations
  4. FEDLEGAL: The First Real-World Federated Learning Benchmark for Legal NLP ↗Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetZhuo Zhang et al.2023 · 33 citations

 Co-authors here

12 of 13 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 32 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

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