--- title: "Jingqi Tong · Fudan University — author profile and papers" description: "Jingqi Tong, Fudan University: 3 papers on Elamur Research (2024–2026), h-index 3 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/jingqi-tong/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/jingqi-tong/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Jingqi Tong # Jingqi Tong Jingqi Tong has 3 papers in our library, in 2024–2026, 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/); often with [Chenglin Li](https://md.research.elamur.ai/free/en/authors/chenglin-li/), [Conghui He](https://md.research.elamur.ai/free/en/authors/conghui-he/), [Haitao Li](https://md.research.elamur.ai/free/en/authors/haitao-li/). 3 papers in our library · 2024–2026 [OpenAlex](https://openalex.org/A5113207942) · [**h-index 3**](https://openalex.org/authors/A5113207942) · [32 works](https://openalex.org/works?filter=author.id:A5113207942) · [54 citations](https://openalex.org/works?filter=author.id:A5113207942&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/jingqi-tong/#papers) · [🔗 Cited 58 times in our library](https://md.research.elamur.ai/free/en/authors/jingqi-tong/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6914](https://md.research.elamur.ai/free/en/paper-stars/page/70/#star-6914) 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=Jingqi+Tong) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Jingqi+Tong) · [dblp](https://dblp.org/search?q=Jingqi+Tong) · [ACL Anthology](https://aclanthology.org/search/?q=Jingqi+Tong) ## Affiliations [🎓**Fudan University** Shanghai · China 2024–2026 · 15 papers*current*](https://md.research.elamur.ai/free/en/universities/fudan-university/) 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 7 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/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) 🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/jingqi-tong/year/2026/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/jingqi-tong/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-Training](https://md.research.elamur.ai/free/en/papers/zhu-2024-llama-moe-building-mixture-experts/)** *(2024 · 85 citations)* Training sparse Mixture-of-Experts (MoE) language models from scratch needs a lot of data and can be unstable. 2. **[VideoPro: Adaptive Program Reasoning for Long Video Understanding](https://md.research.elamur.ai/free/en/papers/li-2026-videopro-adaptive-program-reasoning-long/)** *(2026 · 6 citations)* Long videos are hard for VideoLLMs because the visual cues needed to answer a question are few and scattered across a long timeline. 3. **[LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-llmeval-fair-large-scale-longitudinal/)** *(2026 · 3 citations)* Fixed public test sets can leak into training corpora and be overfitted, so leaderboard scores may overstate real LLM ability. ## All works 4 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. **[LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-Training](https://md.research.elamur.ai/free/en/papers/zhu-2024-llama-moe-building-mixture-experts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tong Zhu, Xiaoye Qu, Daize Dong, et al.*2024 · 85 citations* 2. **[VideoPro: Adaptive Program Reasoning for Long Video Understanding](https://md.research.elamur.ai/free/en/papers/li-2026-videopro-adaptive-program-reasoning-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenglin Li, Feng Han, Yikun Wang, et al.*2026 · 6 citations* 3. **[LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-llmeval-fair-large-scale-longitudinal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Zhang, Yujiong Shen, Jingyi Deng, et al.*2026 · 3 citations* 4. **[FARS: A Fully Automated Research System Deployed at Scale ↗](https://arxiv.org/abs/2606.31651) arXiv:2606.31651 · no summary yet**Qiong Tang et al.*2026 · 1 citation* ## Co-authors here 12 of 16 co-authors with a page, the most papers together first. - [Chenglin Li](https://md.research.elamur.ai/free/en/authors/chenglin-li/) - [Conghui He](https://md.research.elamur.ai/free/en/authors/conghui-he/) - [Haitao Li](https://md.research.elamur.ai/free/en/authors/haitao-li/) - [Haowen Hou](https://md.research.elamur.ai/free/en/authors/haowen-hou/) - [Jiaqi Wang](https://md.research.elamur.ai/free/en/authors/jiaqi-wang/) - [Junzhe Wang](https://md.research.elamur.ai/free/en/authors/junzhe-wang/) - [Ming Zhang](https://md.research.elamur.ai/free/en/authors/ming-zhang/) - [Qianglong Chen](https://md.research.elamur.ai/free/en/authors/qianglong-chen/) - [Shichun Liu](https://md.research.elamur.ai/free/en/authors/shichun-liu/) - [Shuai Dong](https://md.research.elamur.ai/free/en/authors/shuai-dong/) - [Tong Zhu](https://md.research.elamur.ai/free/en/authors/tong-zhu/) - [Xiaoye Qu](https://md.research.elamur.ai/free/en/authors/xiaoye-qu/) ## 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/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2 - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2024](https://md.research.elamur.ai/free/en/venues/emnlp/2024/) ## Cited by Papers of our library cite their works 58 times (of the 149,439 papers whose bibliographies we read); [15 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/jingqi-tong/cited-by/). Updated 31 October 2026