--- title: "Shuchang Tao · Alibaba Group — author profile and papers" description: "Shuchang Tao, Alibaba Group: 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/shuchang-tao/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/shuchang-tao/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Shuchang Tao # Shuchang Tao Shuchang Tao 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/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Bolin Ding](https://md.research.elamur.ai/free/en/authors/bolin-ding/), [Aiwei Liu](https://md.research.elamur.ai/free/en/authors/aiwei-liu/), [Bingbing Xu](https://md.research.elamur.ai/free/en/authors/bingbing-xu/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5120316587) · [**h-index 0**](https://openalex.org/authors/A5120316587) · [6 works](https://openalex.org/works?filter=author.id:A5120316587) · [0 citations](https://openalex.org/works?filter=author.id:A5120316587&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/shuchang-tao/#papers) · 🔗 Cited 4 times in our library · [⭐ Paper Stars ranking: #10761](https://md.research.elamur.ai/free/en/paper-stars/page/108/#star-10761) 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=Shuchang+Tao) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Shuchang+Tao) · [dblp](https://dblp.org/search?q=Shuchang+Tao) · [ACL Anthology](https://aclanthology.org/search/?q=Shuchang+Tao) ## Affiliations [🏢**Alibaba Group** Hangzhou · China 2025–2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group/) · [🏢**Alibaba Group** George Town · Cayman Islands 2025–2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group-cayman-islands/) 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 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [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/) · [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 · 1 work](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/shuchang-tao/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[d-TreeRPO: Towards More Reliable Policy Optimization for Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/pan-2026-d-treerpo-more-reliable-policy/)** *(2026 · 3 citations)* Reinforcement learning for diffusion large language models (dLLMs) has two weak spots. Rewards are usually sparse outcome scores or unverified process signals, and per-token log-probabilities are approximated without accounting for the expectation over all possible decoding orders. d-TreeRPO addresses both. It… 2. **[Incentivizing Strong Reasoning from Weak Supervision](https://md.research.elamur.ai/free/en/papers/yuan-2026-incentivizing-strong-reasoning-weak-supervision/)** *(2026 · 1 citation)* Improving LLM reasoning usually requires either reinforcement learning with verifiable rewards, which is compute-intensive, or SFT on long chain-of-thought (CoT) data from very strong teachers, which is costly to obtain. ## Co-authors here 10 co-authors with a page, the most papers together first. - [Bolin Ding](https://md.research.elamur.ai/free/en/authors/bolin-ding/) ×2 - [Aiwei Liu](https://md.research.elamur.ai/free/en/authors/aiwei-liu/) - [Bingbing Xu](https://md.research.elamur.ai/free/en/authors/bingbing-xu/) - [Jinyang Gao](https://md.research.elamur.ai/free/en/authors/jinyang-gao/) - [Leyi Pan](https://md.research.elamur.ai/free/en/authors/leyi-pan/) - [Liancheng Fang](https://md.research.elamur.ai/free/en/authors/liancheng-fang/) - [Lijie Wen](https://md.research.elamur.ai/free/en/authors/lijie-wen/) - [Teng Xiao](https://md.research.elamur.ai/free/en/authors/teng-xiao/) - [Yige Yuan](https://md.research.elamur.ai/free/en/authors/yige-yuan/) - [Zhaoyang Liu](https://md.research.elamur.ai/free/en/authors/zhaoyang-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/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/): [EACL 2026](https://md.research.elamur.ai/free/en/venues/eacl/2026/) ## Cited by Papers of our library cite their works 4 times (of the 149,439 papers whose bibliographies we read). Updated 1 November 2026