--- title: "Quan Shi — author profile and papers — Elamur Research" description: "Quan Shi: 2 papers on Elamur Research (2024) — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/quan-shi/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/quan-shi/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Quan Shi # Quan Shi Quan Shi has 2 papers in our library, in 2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Michael Tang](https://md.research.elamur.ai/free/en/authors/michael-tang/), [Hongjin Su](https://md.research.elamur.ai/free/en/authors/hongjin-su/), [Howard Yen](https://md.research.elamur.ai/free/en/authors/howard-yen/). 2 papers in our library · 2024 No OpenAlex profile matched yet. [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/quan-shi/#papers) · [🔗 Cited 98 times in our library](https://md.research.elamur.ai/free/en/authors/quan-shi/cited-by/) · [⭐ Paper Stars ranking: #7833](https://md.research.elamur.ai/free/en/paper-stars/page/79/#star-7833) 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=Quan+Shi) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Quan+Shi) · [dblp](https://dblp.org/search?q=Quan+Shi) · [ACL Anthology](https://aclanthology.org/search/?q=Quan+Shi) ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 6 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Information Systems · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Science Applications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-science-applications/) 🧭 Topics 4 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) 💡 Concepts 1 Key ideas and methods explained on our concept pages.[Inverted index · 1 work](https://md.research.elamur.ai/free/en/concepts/inverted-index/) ## Works by year ### 2020s [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/quan-shi/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval](https://md.research.elamur.ai/free/en/papers/su-2024-bright-realistic-challenging-benchmark-reasoning/)** *(2024 · 77 citations)* Standard retrieval benchmarks such as BEIR and MTEB mostly test search-engine-style questions. In these, relevant documents share many words or meanings with the query. Many real needs are harder. A programmer may need documentation for a function that is never named in the question, or a student may need a problem… 2. **[Can Language Models Solve Olympiad Programming?](https://md.research.elamur.ai/free/en/papers/shi-2024-language-models-solve-olympiad-programming/)** *(2024 · 28 citations)* Widely used code benchmarks such as HumanEval and MBPP are now nearly saturated, so they no longer show where language models fall short in algorithmic reasoning. ## Co-authors here 11 co-authors with a page, the most papers together first. - [Michael Tang](https://md.research.elamur.ai/free/en/authors/michael-tang/) ×2 - [Hongjin Su](https://md.research.elamur.ai/free/en/authors/hongjin-su/) - [Howard Yen](https://md.research.elamur.ai/free/en/authors/howard-yen/) - [Jinsung Yoon](https://md.research.elamur.ai/free/en/authors/jinsung-yoon/) - [Karthik Narasimhan](https://md.research.elamur.ai/free/en/authors/karthik-narasimhan/) - [Mengzhou Xia](https://md.research.elamur.ai/free/en/authors/mengzhou-xia/) - [Niklas Muennighoff](https://md.research.elamur.ai/free/en/authors/niklas-muennighoff/) - [Ruoxi Sun](https://md.research.elamur.ai/free/en/authors/ruoxi-sun/) - [Shunyu Yao](https://md.research.elamur.ai/free/en/authors/shunyu-yao/) - [Weijia Shi](https://md.research.elamur.ai/free/en/authors/weijia-shi/) - [Zachary S. Siegel](https://md.research.elamur.ai/free/en/authors/zachary-s-siegel/) ## Cited by Papers of our library cite their works 98 times (of the 149,439 papers whose bibliographies we read); [34 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/quan-shi/cited-by/). Updated 2 November 2026