--- title: "Xianjie Wu — author profile and papers — Elamur Research" description: "Xianjie Wu, Tencent: 4 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/xianjie-wu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/xianjie-wu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Xianjie Wu # Xianjie Wu Xianjie Wu has 4 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Question answering](https://md.research.elamur.ai/free/en/topics/question-answering/), [Multilingual & cross-lingual NLP](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/); often with [Chao Xue](https://md.research.elamur.ai/free/en/authors/chao-xue/), [Chenyao Lu](https://md.research.elamur.ai/free/en/authors/chenyao-lu/), [Di Liang](https://md.research.elamur.ai/free/en/authors/di-liang/). 4 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139822162) · [**h-index 0**](https://openalex.org/authors/A5139822162) · [4 works](https://openalex.org/works?filter=author.id:A5139822162) · [0 citations](https://openalex.org/works?filter=author.id:A5139822162&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/xianjie-wu/#papers) · [🔗 Cited 16 times in our library](https://md.research.elamur.ai/free/en/authors/xianjie-wu/cited-by/) · [⭐ Paper Stars ranking: #10548](https://md.research.elamur.ai/free/en/paper-stars/page/106/#star-10548) 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=Xianjie+Wu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Xianjie+Wu) · [dblp](https://dblp.org/search?q=Xianjie+Wu) · [ACL Anthology](https://aclanthology.org/search/?q=Xianjie+Wu) ## Affiliations [🏢**Tencent** Shenzhen · China 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/companies/tencent/) · [🎓**Beihang University** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/beihang-university/) 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).[Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 4 Research subjects and languages the work is about.[Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Multilingual & cross-lingual NLP · 1 work](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Question answering · 1 work](https://md.research.elamur.ai/free/en/topics/question-answering/) ## Works by year ### 2020s [**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/xianjie-wu/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty](https://md.research.elamur.ai/free/en/papers/xue-2026-reason-only-when-needed-efficient/)** *(2026 · 8 citations)* Generative reward models (GRMs) judge LLM outputs using chain-of-thought (CoT) reasoning. They have two weaknesses. They spend reasoning effort on every input, including easy ones. They also pick among sampled reasoning chains by voting, which cannot separate sound chains from ones that only look convincing. The… 2. **[Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2026-why-supervised-fine-tuning-fails/)** *(2026 · 6 citations)* Supervised fine-tuning (SFT) is usually treated as a reliable way to specialize LLMs. The authors show, however, that converged models still get part of their own training set wrong. They call this the Incomplete Learning Phenomenon (ILP), distinguish it from catastrophic forgetting and machine unlearning, and… 3. **[M3TQA: Massively Multilingual Multitask Table Question Answering](https://md.research.elamur.ai/free/en/papers/shu-2026-m3tqa-massively-multilingual-multitask-table/)** *(2026 · 2 citations)* Research on table question answering with LLMs has focused mostly on English. The few multilingual table benchmarks that exist mainly cover Indo-European or otherwise prominent languages, and they are too small for fine-grained cross-lingual analysis. M3TQA addresses this gap. It starts from 50 real-world tables (41… 4. **[Table-R1: Region-based Reinforcement Learning for Table Understanding](https://md.research.elamur.ai/free/en/papers/wu-2026-table-r1-region-based-reinforcement/)** *(2026)* Large language models still have difficulty answering questions over tables because answers depend on how rows and columns relate. ## Co-authors here 12 of 23 co-authors with a page, the most papers together first. - [Chao Xue](https://md.research.elamur.ai/free/en/authors/chao-xue/) ×2 - [Chenyao Lu](https://md.research.elamur.ai/free/en/authors/chenyao-lu/) ×2 - [Di Liang](https://md.research.elamur.ai/free/en/authors/di-liang/) ×2 - [Haibo Shi](https://md.research.elamur.ai/free/en/authors/haibo-shi/) ×2 - [Jian Yang](https://md.research.elamur.ai/free/en/authors/jian-yang/) ×2 - [Lei Jiang](https://md.research.elamur.ai/free/en/authors/lei-jiang/) ×2 - [Mengqiao Liu](https://md.research.elamur.ai/free/en/authors/mengqiao-liu/) ×2 - [Peiyang Liu](https://md.research.elamur.ai/free/en/authors/peiyang-liu/) ×2 - [Shuang Liang](https://md.research.elamur.ai/free/en/authors/shuang-liang/) ×2 - [Xingsheng Han](https://md.research.elamur.ai/free/en/authors/xingsheng-han/) ×2 - [Yao Wang](https://md.research.elamur.ai/free/en/authors/yao-wang/) ×2 - [Yu Lu](https://md.research.elamur.ai/free/en/authors/yu-lu/) ×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/) ×3: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×3 - [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/) ## Cited by Papers of our library cite their works 16 times (of the 149,439 papers whose bibliographies we read); [7 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/xianjie-wu/cited-by/). Updated 2 November 2026