--- title: "Xingyuan Bu — author profile and papers — Elamur Research" description: "Xingyuan Bu, Beijing Institute of Technology: 3 papers on Elamur Research (2024–2025), h-index 10 — affiliations, topics, co-authors and…" canonical: "https://research.elamur.ai/free/en/authors/xingyuan-bu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/xingyuan-bu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Xingyuan Bu # Xingyuan Bu Xingyuan Bu has 3 papers in our library, in 2024–2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/); often with [Jiaheng Liu](https://md.research.elamur.ai/free/en/authors/jiaheng-liu/), [Yancheng He](https://md.research.elamur.ai/free/en/authors/yancheng-he/), [Bo Zheng](https://md.research.elamur.ai/free/en/authors/bo-zheng/). 3 papers in our library · 2024–2025 [OpenAlex](https://openalex.org/A5039569339) · [ORCID](https://orcid.org/0000-0002-6445-4306) · [**h-index 10**](https://openalex.org/authors/A5039569339) · [54 works](https://openalex.org/works?filter=author.id:A5039569339) · [432 citations](https://openalex.org/works?filter=author.id:A5039569339&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/xingyuan-bu/#papers) · [🔗 Cited 258 times in our library](https://md.research.elamur.ai/free/en/authors/xingyuan-bu/cited-by/) · [2 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #5377](https://md.research.elamur.ai/free/en/paper-stars/page/54/#star-5377) 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=Xingyuan+Bu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Xingyuan+Bu) · [dblp](https://dblp.org/search?q=Xingyuan+Bu) · [ACL Anthology](https://aclanthology.org/search/?q=Xingyuan+Bu) ## Affiliations [🎓**Beijing Institute of Technology** Beijing · China 2008–2026 · 16 papers*current*](https://md.research.elamur.ai/free/en/universities/beijing-institute-of-technology/) · [🎓**Nanjing University of Aeronautics and Astronautics** Nanjing · China 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/nanjing-university-of-aeronautics-and-astronautics/) · [🏢**ByteDance** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/bytedance/) · [🏢**Alibaba Group** Hangzhou · China 2022–2025 · 14 papers](https://md.research.elamur.ai/free/en/companies/alibaba-group/) · [🏢**Sensetime** Beijing · China 2020–2021 · 3 papers](https://md.research.elamur.ai/free/en/companies/sensetime/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 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).[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/) 🧭 Topics 5 Research subjects and languages the work is about.[Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Machine translation · 1 work](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/xingyuan-bu/year/2025/) · [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/xingyuan-bu/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[MT-Bench-101: A Fine-Grained Benchmark for Evaluating Large Language Models in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/bai-2024-mt-bench-101-fine-grained/)** *(2024 · 174 citations)* Existing LLM benchmarks mostly test single-turn instructions. Multi-turn ones such as MT-Bench cover only two turns and broad skill categories, so they miss much of what happens in real chatbot conversations. MT-Bench-101 fills this gap with a fine-grained multi-turn benchmark. The authors studied real user–chatbot… 2. **[Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2024-chinese-simpleqa-chinese-factuality/)** *(2024 · 34 citations)* Hallucination remains a major weakness of large language models. Factuality is hard to measure when models produce long answers that mix many claims. OpenAI's SimpleQA addressed this with short fact-seeking questions, but it covers only English. Chinese SimpleQA is a Chinese counterpart: 3,000 short questions, each… 3. **[Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/)** *(2025 · 30 citations)* Reasoning models in the o1 style produce very long chains of thought (CoT). Until this paper, there was no systematic way to check how good those chains are, or whether other models can find the mistakes in them. The authors built DeltaBench to address both gaps. It contains 1,236 problems from Math, Programming, PCB… ## 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. **[MT-Bench-101: A Fine-Grained Benchmark for Evaluating Large Language Models in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/bai-2024-mt-bench-101-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ge Bai, Jie Liu, Xingyuan Bu, et al.*2024 · 174 citations* 2. **[SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines ↗](https://arxiv.org/abs/2502.14739) arXiv:2502.14739 · no summary yet**M-A-P Team et al.*2025 · 89 citations* 3. [**Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models arXiv:2411.07140**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2024 · 34 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-chinese-simpleqa-chinese-factuality/) 4. **[Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2025 · 30 citations* 5. **[COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human Values ↗](https://aclanthology.org/2026.findings-eacl.288/) Findings of the Association for Computational Linguistics: EACL 2026 · no summary yet**Siwei Wu et al.*2026* ## Co-authors here 12 of 19 co-authors with a page, the most papers together first. - [Jiaheng Liu](https://md.research.elamur.ai/free/en/authors/jiaheng-liu/) ×3 - [Yancheng He](https://md.research.elamur.ai/free/en/authors/yancheng-he/) ×3 - [Bo Zheng](https://md.research.elamur.ai/free/en/authors/bo-zheng/) ×2 - [Shilong Li](https://md.research.elamur.ai/free/en/authors/shilong-li/) ×2 - [Weixun Wang](https://md.research.elamur.ai/free/en/authors/weixun-wang/) ×2 - [Wenbo Su](https://md.research.elamur.ai/free/en/authors/wenbo-su/) ×2 - [Zhuoran Lin](https://md.research.elamur.ai/free/en/authors/zhuoran-lin/) ×2 - [Boren Zheng](https://md.research.elamur.ai/free/en/authors/boren-zheng/) - [Ge Zhang](https://md.research.elamur.ai/free/en/authors/ge-zhang/) - [Hangyu Guo](https://md.research.elamur.ai/free/en/authors/hangyu-guo/) - [Hui Huang](https://md.research.elamur.ai/free/en/authors/hui-huang/) - [Jie Liu](https://md.research.elamur.ai/free/en/authors/jie-liu/) ## 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 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/), [ACL 2024](https://md.research.elamur.ai/free/en/venues/acl/2024/) - Findings of the Association for Computational Linguistics: EACL 2026 ## Cited by Papers of our library cite their works 258 times (of the 149,439 papers whose bibliographies we read); [83 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/xingyuan-bu/cited-by/). Updated 1 November 2026