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Zhiqiang Hu

Zhiqiang Hu has 3 papers in our library, in 2023–2024, most of them on Language models & pretraining, Reasoning, Vision & language; often with Lidong Bing, Chenhui Shen, Guanzheng Chen.

3 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 4 · 9 works · 83 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 300 times in our library · ⭐ Paper Stars ranking: #3122

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

🎓Singapore University of Technology and DesignSingapore · Singapore2024–2025 · 5 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.

 Concepts, shelves and topics

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputational Theory and Mathematics · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 3 worksReasoning · 1 workVision & language · 1 work

 Works by year

2020s

20241 paperMath-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models20232 papersZhiqiang Hu's papers of 2023

 Papers

The most cited first (OpenAlex and our library).

  1. LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models (2023 · 399 citations)
    Fully fine-tuning open LLMs is costly in compute and storage. Parameter-efficient fine-tuning (PEFT) trains only small add-on modules, but it was unclear which PEFT variant, inserted where and with which hyperparameters, works best for modern LLMs. The authors built LLM-Adapters, an open framework that attaches…
  2. SeaLLMs — Large Language Models for Southeast Asia (2023 · 92 citations)
    Mainstream LLMs are trained mostly on English. As a result, they handle Southeast Asian languages poorly, especially those written in non-Latin scripts, which standard BPE tokenizers break into very long token sequences. SeaLLMs are open models for Southeast Asian languages, built by adapting English-centric…
  3. Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models (2024 · 86 citations)
    Open-source multimodal LLMs such as LLaVA-1.5 handle general VQA well but struggle with math problems that depend on diagrams, charts, or tables.

 Co-authors here

12 of 15 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 300 times (of the 141,840 papers whose bibliographies we read); 23 citing papers with a page here →.

Updated

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