Elamur Research⌕
☰
home / authors / Lei Yang

Lei Yang

Lei Yang has 2 papers in our library, in 2026, most of them on Language models & pretraining, Code & programming languages, Semantic parsing & meaning representation; often with Bojian Xiong, Guanhua Chen, Jian Yang.

2 papers in our library · 2026

OpenAlex · h-index 0 · 5 works · 0 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1 time in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #11583

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

🎓Tianjin UniversityTianjin · China2026 · 2 paperscurrent🏢Ant GroupHangzhou · China2026 · 1 papercurrent🎓Southern University of Science and TechnologyShenzhen · China2026 · 1 papercurrent

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

 Fields, topics and concepts

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksSoftware · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workCode & programming languages · 1 workSemantic parsing & meaning representation · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for Tibetan (2026 · 1 citation)
    Mainstream LLMs are trained mostly on high-resource languages, so Tibetan remains poorly served despite its millions of speakers and cultural importance. The authors build an end-to-end pipeline to close this gap.
  2. Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL (2026)
    LLM-based Text-to-SQL systems score well on benchmarks such as Spider and BIRD, but they can still fail in hidden ways.

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. From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for TibetanAnnual Meeting of the Association for Computational Linguistics (ACL)Lei Yang, Leiyu Pan, Bojian Xiong, et al.2026 · 1 citation
  2. Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQLFindings of the Association for Computational LinguisticsHanqing Wang, Yongdong Chi, Jian Yang, et al.2026
  3. Representation-Guided Parameter-Efficient LLM Unlearning ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetZeguan Xiao et al.2026
  4. DVMap: Fine-Grained Pluralistic Value Alignment via High-Consensus Demographic-Value Mapping ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetPengyun Zhu et al.2026

 Co-authors here

11 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 1 time (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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