--- title: "Zhe Tang — author profile and papers — Elamur Research" description: "Zhe Tang: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/zhe-tang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhe-tang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhe Tang # Zhe Tang Zhe Tang has 2 papers in our library, in 2026, 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/); often with [Jiaming Wang](https://md.research.elamur.ai/free/en/authors/jiaming-wang/), [Peng Ding](https://md.research.elamur.ai/free/en/authors/peng-ding/), [Xiaoyu Li](https://md.research.elamur.ai/free/en/authors/xiaoyu-li/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5120722389) · [**h-index 0**](https://openalex.org/authors/A5120722389) · [1 works](https://openalex.org/works?filter=author.id:A5120722389) · [0 citations](https://openalex.org/works?filter=author.id:A5120722389&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/zhe-tang/#papers) · [🔗 Cited 1 time in our library](https://md.research.elamur.ai/free/en/authors/zhe-tang/cited-by/) · [⭐ Paper Stars ranking: #11768](https://md.research.elamur.ai/free/en/paper-stars/page/118/#star-11768) 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=Zhe+Tang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhe+Tang) · [dblp](https://dblp.org/search?q=Zhe+Tang) · [ACL Anthology](https://aclanthology.org/search/?q=Zhe+Tang) ## 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 · 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/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 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/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/zhe-tang/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Meeseeks: A Feedback-Driven, Iterative Self-Correction Benchmark evaluating LLMs' Instruction Following Capability](https://md.research.elamur.ai/free/en/papers/wang-2026-meeseeks-feedback-driven-iterative-self/)** *(2026 · 1 citation)* Large language models often fail to satisfy every requirement in prompts that contain many constraints. Meeseeks is a benchmark that measures how far models can improve when they get repeated, targeted feedback. It works in cycles. The tested model answers a prompt, and each constraint is checked automatically. The… 2. **[SOP-Maze: Evaluating Large Language Models on Complicated Business Standard Operating Procedures](https://md.research.elamur.ai/free/en/papers/wang-2026-sop-maze-evaluating-large-language/)** *(2026)* Most instruction-following benchmarks do not test whether LLMs can carry out the long, branching standard operating procedures (SOPs) used in real business workflows, where user input is often noisy. ## Co-authors here 5 co-authors with a page, the most papers together first. - [Jiaming Wang](https://md.research.elamur.ai/free/en/authors/jiaming-wang/) ×2 - [Peng Ding](https://md.research.elamur.ai/free/en/authors/peng-ding/) ×2 - [Xiaoyu Li](https://md.research.elamur.ai/free/en/authors/xiaoyu-li/) ×2 - [Xuezhi Cao](https://md.research.elamur.ai/free/en/authors/xuezhi-cao/) ×2 - [Yilin Jin](https://md.research.elamur.ai/free/en/authors/yilin-jin/) ×2 ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×2 ## Cited by Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read); [1 citing paper with a page here →](https://md.research.elamur.ai/free/en/authors/zhe-tang/cited-by/). Updated 1 November 2026