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Jianyong Wang

Jianyong Wang has 4 papers in our library, in 2018–2026, most of them on Language models & pretraining, Machine translation, Efficient models & compression; often with Furu Wei, Li Dong, Yuqing Xia.

4 papers in our library · 2018–2026

OpenAlex · ORCID · h-index 47 · 200 works · 12,633 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 242 times in our library · ⭐ Paper Stars ranking: #4082

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. 16 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

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. Retentive Network: A Successor to Transformer for Large Language Models (2023 · 265 citations)
    The authors, from Microsoft Research and Tsinghua University, seek an architecture for large language models that has three properties at once.
  2. Style Transfer as Unsupervised Machine Translation (2018 · 165 citations)
    Text style transfer means rewriting a sentence so that it carries a different attribute, such as positive instead of negative sentiment, while what it says stays the same.
  3. FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling (2025 · 15 citations)
    Speculative sampling speeds up LLM decoding. A small draft model proposes tokens, and the full model checks them in parallel. The authors find that this benefit shrinks for models with big vocabularies, such as Llama-3-8B (128k tokens). They re-implemented EAGLE-2 in native C and CUDA to strip away Python and…
  4. Rectified Sparse Attention for Efficient Long-Sequence Generation (2026 · 1 citation)
    Large language models that produce very long outputs, such as extended reasoning chains, are slowed down by having to read the entire KV cache at every decoding step.

 Co-authors here

12 of 22 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 242 times (of the 149,439 papers whose bibliographies we read); 40 citing papers with a page here →.

Updated

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