Elamur Research⌕
☰
home / authors / Weizhe Lin

Weizhe Lin

Weizhe Lin has 2 papers in our library, in 2026, most of them on Language models & pretraining, Information retrieval & search, Bias, fairness & safety; often with Bill Byrne, Hui-Ling Zhen, Mingxuan Yuan.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 11 · 50 works · 1,459 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 40 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #13175

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

🎓University of CambridgeCambridge · United Kingdom2019–2026 · 28 paperscurrent🏢Huawei TechnologiesShenzhen · China2026 · 3 paperscurrent🏢AppleCupertino · United States2023 · 3 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 8The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksEngineering · 1 workComputational Theory and Mathematics · 1 workComputer Vision and Pattern Recognition · 1 workElectrical and Electronic Engineering · 1 workArtificial Intelligence · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 4Research subjects and languages the work is about.Efficient models & compression · 1 workBias, fairness & safety · 1 workInformation retrieval & search · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Unleashing Low-Bit Inference on Ascend NPUs: A Comprehensive Evaluation of HiFloat Formats (2026 · 1 citation)
    The paper asks whether Huawei's HiFloat number formats, built for Ascend NPUs, work well for post-training quantization (PTQ) of large language models.
  2. Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models (2026)
    Jailbreak attacks keep evolving. Defenders therefore need systems that can absorb new attack styles without retraining and that let operators decide how much benign traffic they are willing to refuse. The authors, from Cambridge, propose Retrieval-Augmented Defense (RAD), a training-free jailbreak detector built on…

All works

4 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. Retrieval Augmented Visual Question Answering with Outside Knowledge ↗Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yetWeizhe Lin, Bill Byrne2022 · 98 citations
  2. More Robust Schema-Guided Dialogue State Tracking via Tree-Based Paraphrase Ranking ↗Findings of the Association for Computational Linguistics: EACL 2023 · no summary yetAlexandru Coca et al.2023 · 3 citations
  3. Unleashing Low-Bit Inference on Ascend NPUs: A Comprehensive Evaluation of HiFloat FormatsAnnual Meeting of the Association for Computational Linguistics (ACL)Pengxiang Zhao, Hui-Ling Zhen, Xing Li, et al.2026 · 1 citation
  4. Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Guangyu Yang, Jinghong Chen, Jingbiao Mei, et al.2026

 Co-authors here

8 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 40 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/weizhe-lin/