--- title: "Lanqing Hong — author profile and papers — Elamur Research" description: "Lanqing Hong, National University of Singapore: 3 papers on Elamur Research (2023–2026), h-index 24 — affiliations, topics, co-authors and…" canonical: "https://research.elamur.ai/free/en/authors/lanqing-hong/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/lanqing-hong/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Lanqing Hong # Lanqing Hong Lanqing Hong has 3 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Jing Li](https://md.research.elamur.ai/free/en/authors/jing-li/), [Baojun Wang](https://md.research.elamur.ai/free/en/authors/baojun-wang/), [Boyang Xue](https://md.research.elamur.ai/free/en/authors/boyang-xue/). 3 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5003882618) · [ORCID](https://orcid.org/0000-0003-2752-5942) · [**h-index 24**](https://openalex.org/authors/A5003882618) · [127 works](https://openalex.org/works?filter=author.id:A5003882618) · [1,739 citations](https://openalex.org/works?filter=author.id:A5003882618&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/lanqing-hong/#papers) · [🔗 Cited 82 times in our library](https://md.research.elamur.ai/free/en/authors/lanqing-hong/cited-by/) · [2 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #8307](https://md.research.elamur.ai/free/en/paper-stars/page/84/#star-8307) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Lanqing+Hong) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Lanqing+Hong) · [dblp](https://dblp.org/search?q=Lanqing+Hong) · [ACL Anthology](https://aclanthology.org/search/?q=Lanqing+Hong) ## Affiliations [🏢**Huawei Technologies** Shenzhen · China 2020–2026 · 59 papers*current*](https://md.research.elamur.ai/free/en/companies/huawei-technologies/) · [🎓**National University of Singapore** Singapore · Singapore 2016–2026 · 13 papers*current*](https://md.research.elamur.ai/free/en/universities/national-university-of-singapore/) · [🔬**Suzhou Research Institute** Suzhou · China 2018–2019 · 3 papers](https://ror.org/03ebk0c60) 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. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 10 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Applied Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/applied-mathematics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) 🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/lanqing-hong/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/lanqing-hong/year/2025/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/lanqing-hong/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model](https://md.research.elamur.ai/free/en/papers/gao-2023-g-llava-solving-geometric-problem/)** *(2023 · 76 citations)* Multimodal LLMs, including GPT-4-V, often misread geometric diagrams. They confuse how points and lines relate, misjudge angles and hallucinate figure contents, so they struggle with geometry problems that require visual input. Public geometry datasets are also small and lack image descriptions. The authors address… 2. **[Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/yu-2025-self-error-instruct-generalizing-errors/)** *(2025 · 5 citations)* LLMs still make many mistakes on math problems. Earlier error-driven methods build new training data from single failed examples, so the data tends to stay tied to those instances. Self-Error-Instruct (SEI) instead groups failures by error type. First, a target model is run on the GSM8K and MATH training sets to… 3. **[AEQ-Bench: Measuring Empathy of Omni-Modal Large Models](https://md.research.elamur.ai/free/en/papers/luo-2026-aeq-bench-measuring-empathy-omni/)** *(2026)* Omni-modal large models (OLMs) increasingly talk to users through speech, yet evaluations of empathy usually turn audio into transcripts and ignore how something is said. ## All works 5 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them. 1. **[DDP: Diffusion Model for Dense Visual Prediction ↗](https://doi.org/10.1109/iccv51070.2023.01987) IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yet**Yuanfeng Ji et al.*2023 · 153 citations* 2. [**G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model arXiv:2312.11370**Jiahui Gao, Renjie Pi, Jipeng Zhang, et al.*2023 · 76 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-g-llava-solving-geometric-problem/) 3. **[MetaBEV: Solving Sensor Failures for 3D Detection and Map Segmentation ↗](https://doi.org/10.1109/iccv51070.2023.00801) IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yet**Chongjian Ge et al.*2023 · 67 citations* 4. **[Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/yu-2025-self-error-instruct-generalizing-errors/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erxin Yu, Jing Li, Ming Liao, et al.*2025 · 5 citations* 5. **[AEQ-Bench: Measuring Empathy of Omni-Modal Large Models](https://md.research.elamur.ai/free/en/papers/luo-2026-aeq-bench-measuring-empathy-omni/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Luo, Lewei Yao, Lanqing Hong, et al.*2026* ## Co-authors here 12 of 19 co-authors with a page, the most papers together first. - [Jing Li](https://md.research.elamur.ai/free/en/authors/jing-li/) ×2 - [Baojun Wang](https://md.research.elamur.ai/free/en/authors/baojun-wang/) - [Boyang Xue](https://md.research.elamur.ai/free/en/authors/boyang-xue/) - [Fei Mi](https://md.research.elamur.ai/free/en/authors/fei-mi/) - [Hang Xu](https://md.research.elamur.ai/free/en/authors/hang-xu/) - [Jiacheng Ye](https://md.research.elamur.ai/free/en/authors/jiacheng-ye/) - [Jiahui Gao](https://md.research.elamur.ai/free/en/authors/jiahui-gao/) - [Jipeng Zhang](https://md.research.elamur.ai/free/en/authors/jipeng-zhang/) - [Kai Chen](https://md.research.elamur.ai/free/en/authors/kai-chen/) - [Lewei Yao](https://md.research.elamur.ai/free/en/authors/lewei-yao/) - [Lifeng Shang](https://md.research.elamur.ai/free/en/authors/lifeng-shang/) - [Lingpeng Kong](https://md.research.elamur.ai/free/en/authors/lingpeng-kong/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - IEEE/CVF International Conference on Computer Vision (ICCV) ×2 - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ## Cited by Papers of our library cite their works 82 times (of the 149,439 papers whose bibliographies we read); [31 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/lanqing-hong/cited-by/). Updated 2 November 2026