Elamur Research⌕
☰
home / authors / Jingping Liu

Jingping Liu

Jingping Liu has 3 papers in our library, in 2025–2026, most of them on Reasoning, Vision & language, Language models & pretraining; often with Yan Zhou, Ziyan Liu, Haiyun Jiang.

3 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 2 · 4 works · 44 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 6 times in our library · ⭐ Paper Stars ranking: #7739

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

🎓East China University of Science and TechnologyShanghai · China2025 · 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksComputer Vision and Pattern Recognition · 3 worksLanguage and Linguistics · 3 works

🧭 Topics 3Research subjects and languages the work is about.Reasoning · 2 worksVision & language · 2 worksLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models (2025 · 41 citations)
    This survey, written by researchers at several Chinese universities and Swinburne University, explains why DeepSeek's V3 and R1 models drew so much attention and what they suggest about the direction of large AI models.
  2. Can Multimodal Large Language Models Understand Spatial Relations? (2025 · 11 citations)
    Spatial relation reasoning is a basic skill for multimodal large language models (MLLMs), but existing benchmarks have several weaknesses.
  3. MirrorQA: Benchmarking Multimodal LLMs on Mirror-Orientation Reasoning (2026)
    Multimodal LLMs often confuse left and right when a question concerns a person's or animal's own body. They tend to answer from the viewer's side of the image rather than the subject's. Existing spatial benchmarks (e.g., EmbSpatial-Bench, VSR) define directions from the camera's viewpoint, and pose datasets like COCO…

 Co-authors here

12 of 13 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 6 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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