Elamur Research⌕
☰
home / authors / Haifeng Sun

Haifeng Sun

Haifeng Sun has 2 papers in our library, in 2026, most of them on Language models & pretraining, Low-resource languages; often with Jianxin Liao, Jingyu Wang, Cong Liu.

2 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 30 · 241 works · 3,400 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 49 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #11520

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

🎓Beijing University of Posts and TelecommunicationsBeijing · China2012–2026 · 217 paperscurrent🔬State Key Laboratory of Networking and Switching TechnologyBeijing · China2012–2026 · 161 paperscurrent

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

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksLow-resource languages · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language Models (2026 · 1 citation)
    The paper tackles a weakness in LLM machine unlearning: current techniques tend to suppress only the literal wording of the data to be forgotten.
  2. ModularMoE: Fast LLM Customization with Parameter-Sharing Mixture-of-Experts for Low-Resource Settings (2026)
    Running large language models on modest hardware is costly. Current customization routes either compress and fine-tune separately for every target task, which is expensive, or tune once on general data, which tends to hurt task-level quality through interference and forgetting. ModularMoE addresses this by turning an…

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. Adversarial and Domain-Aware BERT for Cross-Domain Sentiment Analysis ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetChunning Du et al.2020 · 203 citations
  2. Capsule Network with Interactive Attention for Aspect-Level Sentiment Classification ↗Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yetChunning Du et al.2019 · 94 citations
  3. Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Huazheng Wang, Yongcheng Jing, Haifeng Sun, et al.2026 · 1 citation
  4. ModularMoE: Fast LLM Customization with Parameter-Sharing Mixture-of-Experts for Low-Resource SettingsFindings of the Association for Computational LinguisticsJiaxing Liu, Qi Qi, Haifeng Sun, et al.2026

 Co-authors here

9 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 49 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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