Elamur Research⌕
☰
home / authors / Qiwei Ye

Qiwei Ye

Qiwei Ye has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining, Vision & language, Efficient models & compression; often with Hui Wang, Kai Chen, Peitian Zhang.

2 papers in our library · 2024–2026

OpenAlex · h-index 2 · 9 works · 89 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 45 times in our library · ⭐ Paper Stars ranking: #7836

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 Academy of Artificial IntelligenceBeijing · China2024–2026 · 3 paperscurrent

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 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 1 workComputer Science · 1 workArtificial Intelligence · 1 workComputer Vision and Pattern Recognition · 1 workLanguage and Linguistics · 1 workBiochemistry, Genetics and Molecular Biology · 1 workMolecular Biology · 1 work

🧭 Topics 3Research subjects and languages the work is about.Efficient models & compression · 1 workLanguage models & pretraining · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Long Context Compression with Activation Beacon (2024 · 47 citations)
    Long inputs are costly for transformer LLMs. Self-attention cost grows quadratically, and holding the KV cache for the whole sequence takes a lot of GPU memory. Earlier context compression methods have several weaknesses:
  2. STELLA: A Multimodal LLM for Protein Functional Annotation via Unified Sequence-Structure Encoding (2026 · 2 citations)
    STELLA addresses protein functional annotation. Protein language models capture biophysical signals well but seldom connect them to the textual knowledge that describes what a protein does. Earlier protein–text multimodal LLMs used separate sequence and structure encoders, which needed fusion layers. STELLA instead…

 Co-authors here

7 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 45 times (of the 149,439 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated

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