--- title: "Leilei Gan · Zhejiang University — author profile and papers" description: "Leilei Gan, Zhejiang University: 4 papers on Elamur Research (2025–2026), h-index 10 — affiliations, topics, co-authors and who cites them…" canonical: "https://research.elamur.ai/free/en/authors/leilei-gan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/leilei-gan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Leilei Gan # Leilei Gan Leilei Gan has 4 papers in our library, in 2025–2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Wenyi Xiao](https://md.research.elamur.ai/free/en/authors/wenyi-xiao/), [Yandi Wang](https://md.research.elamur.ai/free/en/authors/yandi-wang/), [Ziwei Huang](https://md.research.elamur.ai/free/en/authors/ziwei-huang/). 4 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5063264979) · [ORCID](https://orcid.org/0000-0001-5859-2588) · [**h-index 10**](https://openalex.org/authors/A5063264979) · [50 works](https://openalex.org/works?filter=author.id:A5063264979) · [344 citations](https://openalex.org/works?filter=author.id:A5063264979&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/leilei-gan/#papers) · [🔗 Cited 70 times in our library](https://md.research.elamur.ai/free/en/authors/leilei-gan/cited-by/) · [5 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #11236](https://md.research.elamur.ai/free/en/paper-stars/page/113/#star-11236) 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=Leilei+Gan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Leilei+Gan) · [dblp](https://dblp.org/search?q=Leilei+Gan) · [ACL Anthology](https://aclanthology.org/search/?q=Leilei+Gan) ## Affiliations [🎓**Zhejiang University** Hangzhou · China 2020–2026 · 44 papersEmployment*current*](https://md.research.elamur.ai/free/en/universities/zhejiang-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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 5 The field of science this work belongs to (OpenAlex fields).[Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Computer Vision and Pattern Recognition · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [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/) 🧭 Topics 3 Research subjects and languages the work is about.[Vision & language · 2 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Reasoning · 3 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/leilei-gan/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/leilei-gan/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts](https://md.research.elamur.ai/free/en/papers/huang-2025-t2i-factualbench-benchmarking-factuality-text/)** *(2025 · 8 citations)* Most text-to-image (T2I) evaluation measures prompt alignment, image quality or object composition. It rarely checks whether models depict specific real-world entities correctly, such as a particular handbag model, landmark or dog breed. To fill this gap, the authors built T2I-FactualBench, which they describe as the… 2. **[REVEALER: Reinforcement-Guided Visual Reasoning for Element-Level Text-Image Alignment Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-revealer-reinforcement-guided-visual-reasoning/)** *(2026 · 1 citation)* Checking whether a text-to-image (T2I) output matches its prompt is usually done with single-number similarity scores or template-driven QA pipelines. 3. **[From Recognition to Reasoning: Benchmarking and Enhancing MLLMs on Real-World Receipt Document Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-recognition-reasoning-benchmarking-enhancing-mllms/)** *(2026)* The paper addresses Visual Information Extraction (VIE) from receipts and invoices. Existing benchmarks are small, synthetic, or limited to narrow domains, and they mostly test literal text extraction. The authors introduce ReceiptBench, a human-annotated collection of 10,656 real-world financial documents, including… 4. **[VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models Reasoning](https://md.research.elamur.ai/free/en/papers/xiao-2026-vl-calibration-decoupled-confidence-calibration/)** *(2026)* Vision-language models often give wrong answers while sounding certain. Existing methods that teach models to state their confidence were built for text-only LLMs and produce one overall score. For multimodal reasoning this score is ambiguous: an error may come from misreading the image or from faulty logic applied… ## All works 9 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them. 1. **[Judgment Prediction via Injecting Legal Knowledge into Neural Networks ↗](https://doi.org/10.1609/aaai.v35i14.17522) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Leilei Gan et al.*2021 · 86 citations* 2. **[Exploiting Contrastive Learning and Numerical Evidence for Confusing Legal Judgment Prediction ↗](https://aclanthology.org/2023.findings-emnlp.814/) Findings of the Association for Computational Linguistics: EMNLP 2023 · no summary yet**Leilei Gan et al.*2023 · 22 citations* 3. **[Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering ↗](https://arxiv.org/abs/2501.06521) arXiv:2501.06521 · no summary yet**Yinghao Hu et al.*2025 · 18 citations* 4. **[T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts](https://md.research.elamur.ai/free/en/papers/huang-2025-t2i-factualbench-benchmarking-factuality-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwei Huang, Wanggui He, Quanyu Long, et al.*2025 · 8 citations* 5. **[Evaluating Test-Time Scaling LLMs for Legal Reasoning: OpenAI o1, DeepSeek-R1, and Beyond ↗](https://aclanthology.org/2025.findings-emnlp.742/) Findings of the Association for Computational Linguistics: EMNLP 2025 · no summary yet**Yinghao Hu et al.*2025 · 8 citations* 6. **[Investigating the Robustness of Natural Language Generation from Logical Forms via Counterfactual Samples ↗](https://aclanthology.org/2022.emnlp-main.370/) Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yet**Chengyuan Liu et al.*2022 · 2 citations* 7. **[REVEALER: Reinforcement-Guided Visual Reasoning for Element-Level Text-Image Alignment Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-revealer-reinforcement-guided-visual-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**FuLin Shi, Wenyi Xiao, Leilei Gan, et al.*2026 · 1 citation* 8. **[From Recognition to Reasoning: Benchmarking and Enhancing MLLMs on Real-World Receipt Document Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-recognition-reasoning-benchmarking-enhancing-mllms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yandi Wang, Libin Zhan, Ziwei Huang, et al.*2026* 9. **[VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models Reasoning](https://md.research.elamur.ai/free/en/papers/xiao-2026-vl-calibration-decoupled-confidence-calibration/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenyi Xiao, Xinchi XU, Leilei Gan*2026* ## Co-authors here 7 co-authors with a page, the most papers together first. - [Wenyi Xiao](https://md.research.elamur.ai/free/en/authors/wenyi-xiao/) ×2 - [Yandi Wang](https://md.research.elamur.ai/free/en/authors/yandi-wang/) ×2 - [Ziwei Huang](https://md.research.elamur.ai/free/en/authors/ziwei-huang/) ×2 - [Fei Qing Wu](https://md.research.elamur.ai/free/en/authors/fei-qing-wu/) - [Jun Chen](https://md.research.elamur.ai/free/en/authors/jun-chen/) - [Liang Ding](https://md.research.elamur.ai/free/en/authors/liang-ding/) - [Yuxuan Jiang](https://md.research.elamur.ai/free/en/authors/yuxuan-jiang/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×4: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×3, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) - Findings of the Association for Computational Linguistics: EMNLP 2023 ×2 - Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing - Proceedings of the AAAI Conference on Artificial Intelligence ## Cited by Papers of our library cite their works 70 times (of the 149,439 papers whose bibliographies we read); [7 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/leilei-gan/cited-by/). Updated 2 November 2026