--- title: "Weiqin Wang · Shenzhen University — author profile and papers" description: "Weiqin Wang, Shenzhen University: 2 papers on Elamur Research (2026), h-index 2 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/weiqin-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/weiqin-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Weiqin Wang # Weiqin Wang Weiqin Wang 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/); often with [Hui Huang](https://md.research.elamur.ai/free/en/authors/hui-huang/), [Yile Wang](https://md.research.elamur.ai/free/en/authors/yile-wang/), [Sijie Cheng](https://md.research.elamur.ai/free/en/authors/sijie-cheng/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5102066583) · [**h-index 2**](https://openalex.org/authors/A5102066583) · [9 works](https://openalex.org/works?filter=author.id:A5102066583) · [12 citations](https://openalex.org/works?filter=author.id:A5102066583&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/weiqin-wang/#papers) · [🔗 Cited 4 times in our library](https://md.research.elamur.ai/free/en/authors/weiqin-wang/cited-by/) · [⭐ Paper Stars ranking: #10776](https://md.research.elamur.ai/free/en/paper-stars/page/108/#star-10776) 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=Weiqin+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Weiqin+Wang) · [dblp](https://dblp.org/search?q=Weiqin+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Weiqin+Wang) ## Affiliations [🎓**Shenzhen University** Shenzhen · China 2025–2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/universities/shenzhen-university/) · [🎓**Hunan Agricultural University** Changsha · China 2025–2026 · 3 papers*current*](https://ror.org/01dzed356) 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 5 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/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/weiqin-wang/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Beyond Majority Voting: Towards Fine-grained and More Reliable Reward Signal for Test-Time Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-beyond-majority-voting-fine-grained/)** *(2026 · 4 citations)* Test-time reinforcement learning (TTRL) trains LLMs on reasoning tasks without gold answers. It samples many responses and treats the majority-voted answer as a pseudo-label. This has two weaknesses. Every vote counts equally, so a popular but wrong answer gets reinforced (confirmation bias), and the binary match… 2. **[AnchorMem: Anchored Facts with Associative Contexts for Building Memory in Large Language Models](https://md.research.elamur.ai/free/en/papers/shen-2026-anchormem-anchored-facts-associative-contexts/)** *(2026)* LLM memory systems such as A-Mem and Mem0 repeatedly summarize and rewrite past interactions. This can wash out fine details. Entity-graph indexing, as in HippoRAG 2, can instead link unrelated memories through common, generic entities. AnchorMem addresses both problems by separating what is used for retrieval from… ## Co-authors here 4 co-authors with a page, the most papers together first. - [Hui Huang](https://md.research.elamur.ai/free/en/authors/hui-huang/) ×2 - [Yile Wang](https://md.research.elamur.ai/free/en/authors/yile-wang/) ×2 - [Sijie Cheng](https://md.research.elamur.ai/free/en/authors/sijie-cheng/) - [Zhicheng Guo](https://md.research.elamur.ai/free/en/authors/zhicheng-guo/) ## 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/) - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ## Cited by Papers of our library cite their works 4 times (of the 149,439 papers whose bibliographies we read); [2 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/weiqin-wang/cited-by/). Updated 1 November 2026