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Lu Hou

Lu Hou has 2 papers in our library, in 2020–2021, most of them on Efficient models & compression; often with Lifeng Shang, Qun Liu, Wei Zhang.

2 papers in our library · 2020–2021

OpenAlex · ORCID · Wikidata · h-index 11 · 28 works · 535 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 139 times in our library · ⭐ Paper Stars ranking: #3838

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

🏢Huawei TechnologiesShenzhen · China2019–2026 · 48 paperscurrent🎓Hong Kong University of Science and TechnologyHong Kong · Hong Kong2016–2022 · 3 papers🎓University of Hong KongPok Fu Lam · Hong Kong2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Efficient models & compression · 2 works

 Works by year

2020s

20211 paperBinaryBERT: Pushing the Limit of BERT Quantization20201 paperTernaryBERT: Distillation-aware Ultra-low Bit BERT

 Papers

The most cited first (OpenAlex and our library).

  1. TernaryBERT: Distillation-aware Ultra-low Bit BERT (2020 · 213 citations)
    Fine-tuned BERT models are large: BERT-base has 109M parameters, over 400 MB in 32-bit floats. This makes them hard to run on phones and other constrained hardware. Earlier quantization work kept accuracy at 8 bits. Going lower usually needed mixed precision, which some hardware handles poorly, or product…
  2. BinaryBERT: Pushing the Limit of BERT Quantization (2021 · 165 citations)
    Large pre-trained language models are hard to run on edge devices, and quantization shrinks them without redesigning the architecture.

 Co-authors here

5 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 139 times (of the 141,840 papers whose bibliographies we read); 9 citing papers with a page here →.

Updated

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