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Yongbin Liu

Yongbin Liu has 2 papers in our library, in 2026, most of them on Evaluation & benchmarks, Reasoning, Efficient models & compression; often with Haodong Zou, Jie Chen, Jie Wang.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 14 · 69 works · 523 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #14073

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

🎓University of South ChinaHengyang · China2016–2026 · 49 paperscurrent🎓Tsinghua UniversityBeijing · China2013–2017 · 5 papers🎓Beijing University of Posts and TelecommunicationsBeijing · China2014–2022 · 3 papers🎓Peking UniversityBeijing · China2016 · 2 papers🎓Tianjin University of Finance and EconomicsTianjin · China2009–2012 · 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.

 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 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 3Research subjects and languages the work is about.Efficient models & compression · 1 workEvaluation & benchmarks · 1 workReasoning · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Latent semantic indexing · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. CompTab: A Comprehensive Benchmark for Real-World TableQA with Complex Reasoning and Irregular Tables (2026)
    Most TableQA benchmarks use tidy, well-formed tables, so they overstate how well LLMs handle the messy tables found in practice.
  2. RanLoRA: Residual-aware Nonlinear Low-Rank Adaptation (2026)
    LoRA restricts weight updates to a linear low-rank subspace, which can limit how well it adapts to complex tasks, especially at very small ranks.

 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.

Updated

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