--- title: "Ruobing Xie — author profile and papers — Elamur Research" description: "Ruobing Xie, Tencent: 4 papers on Elamur Research (2017–2026), h-index 37 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/ruobing-xie/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ruobing-xie/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ruobing Xie # Ruobing Xie Ruobing Xie has 4 papers in our library, in 2017–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Knowledge graphs & ontologies](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/); often with [Jiaqi Zhu](https://md.research.elamur.ai/free/en/authors/jiaqi-zhu/), [Shuaipeng Li](https://md.research.elamur.ai/free/en/authors/shuaipeng-li/), [Xingwu Sun](https://md.research.elamur.ai/free/en/authors/xingwu-sun/). 4 papers in our library · 2017–2026 [OpenAlex](https://openalex.org/A5101577090) · [ORCID](https://orcid.org/0000-0003-3170-5647) · [Wikidata](https://www.wikidata.org/wiki/Q130799640) · [**h-index 37**](https://openalex.org/authors/A5101577090) · [174 works](https://openalex.org/works?filter=author.id:A5101577090) · [5,290 citations](https://openalex.org/works?filter=author.id:A5101577090&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/ruobing-xie/#papers) · [🔗 Cited 1,130 times in our library](https://md.research.elamur.ai/free/en/authors/ruobing-xie/cited-by/) · [10 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6283](https://md.research.elamur.ai/free/en/paper-stars/page/63/#star-6283) 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=Ruobing+Xie) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ruobing+Xie) · [dblp](https://dblp.org/search?q=Ruobing+Xie) · [ACL Anthology](https://aclanthology.org/search/?q=Ruobing+Xie) ## Affiliations [🏢**Tencent** Shenzhen · China 2017–2026 · 148 papersEmployment since 2017 · Senior Researcher*current*](https://md.research.elamur.ai/free/en/companies/tencent/) · [🎓**Tsinghua University** Beijing · China 2010–2024 · 11 papersEducation 2010–2017](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) · [🔬**State Key Laboratory of Intelligent Technology and Systems** Beijing · China 2016–2017 · 6 papers](https://md.research.elamur.ai/free/en/labs/state-key-laboratory-of-intelligent-technology-and-systems/) · [🏛️**Chinese Academy of Sciences** Beijing · China 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🔬**Institute of Computing Technology** Beijing · China 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/labs/institute-of-computing-technology/) 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 · 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 · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 2 Research subjects and languages the work is about.[Knowledge graphs & ontologies · 1 work](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/ruobing-xie/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/ruobing-xie/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/ruobing-xie/year/2024/) ### 2010s [**2017** 1 paper](https://md.research.elamur.ai/free/en/authors/ruobing-xie/year/2017/) ## Papers The most cited first (OpenAlex and our library). 1. **[Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence](https://md.research.elamur.ai/free/en/papers/xie-2017-william-shakespeare-really-write-hamlet/)** *(2017 · 93 citations)* Large knowledge graphs such as Freebase are increasingly filled by automatic extraction and crowdsourcing, so they contain wrong or conflicting facts. 2. **[Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent](https://md.research.elamur.ai/free/en/papers/sun-2024-hunyuan-large-open-source/)** *(2024 · 25 citations)* Most open-source LLMs use dense architectures, and the few public mixture-of-experts (MoE) models are relatively small. 3. **[Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation](https://md.research.elamur.ai/free/en/papers/zhang-2026-find-your-optimal-teacher-personalized/)** *(2026 · 13 citations)* Small LLMs are usually distilled by fine-tuning them on outputs from the most powerful available teacher. Prior work shows this can backfire: very strong teachers may produce answers that are too complex or too far from what the student can absorb. Earlier remedies (Mix, CAR) still make every candidate teacher answer… 4. **[HMoE: Heterogeneous Mixture of Experts for Language Modeling](https://md.research.elamur.ai/free/en/papers/wang-2025-hmoe-heterogeneous-mixture-experts-language/)** *(2025 · 11 citations)* Standard Mixture of Experts (MoE) language models use experts of identical size, even though some tokens are harder to process than others. ## All works 14 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them. 1. **[Representation Learning of Knowledge Graphs with Entity Descriptions ↗](https://doi.org/10.1609/aaai.v30i1.10329) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Ruobing Xie et al.*2016 · 776 citations* 2. **[Iterative Entity Alignment via Joint Knowledge Embeddings ↗](https://doi.org/10.24963/ijcai.2017/595) International Joint Conference on Artificial Intelligence · no summary yet**Hao Zhu et al.*2017 · 407 citations* 3. **[Large Language Models are Zero-Shot Rankers for Recommender Systems ↗](https://arxiv.org/abs/2305.08845) arXiv:2305.08845 · no summary yet**Yupeng Hou et al.*2023 · 394 citations* 4. **[Image-embodied Knowledge Representation Learning ↗](https://doi.org/10.24963/ijcai.2017/438) International Joint Conference on Artificial Intelligence · no summary yet**Ruobing Xie et al.*2017 · 298 citations* 5. **[Improved Word Representation Learning with Sememes ↗](https://aclanthology.org/P17-1187/) Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Yilin Niu et al.*2017 · 140 citations* 6. **[Advancing LLM Reasoning Generalists with Preference Trees ↗](https://arxiv.org/abs/2404.02078) arXiv:2404.02078 · no summary yet**Lifan Yuan et al.*2024 · 94 citations* 7. **[Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence](https://md.research.elamur.ai/free/en/papers/xie-2017-william-shakespeare-really-write-hamlet/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Ruobing Xie, Zhiyuan Liu, Fen Lin, et al.*2017 · 93 citations* 8. **[Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised Data ↗](https://aclanthology.org/D19-1021/) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yet**Ruidong Wu et al.*2019 · 84 citations* 9. **[Hierarchical Reinforcement Learning for Integrated Recommendation ↗](https://doi.org/10.1609/aaai.v35i5.16580) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Ruobing Xie et al.*2021 · 79 citations* 10. **[Connecting Embeddings for Knowledge Graph Entity Typing ↗](https://aclanthology.org/2020.acl-main.572/) Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yet**Yu Zhao et al.*2020 · 67 citations* 11. [**Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent arXiv:2411.02265**Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-hunyuan-large-open-source/) 12. **[Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation](https://md.research.elamur.ai/free/en/papers/zhang-2026-find-your-optimal-teacher-personalized/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hengyuan Zhang, Shiping Yang, Xiao Liang, et al.*2026 · 13 citations* 13. **[HMoE: Heterogeneous Mixture of Experts for Language Modeling](https://md.research.elamur.ai/free/en/papers/wang-2025-hmoe-heterogeneous-mixture-experts-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**An Wang, Xingwu Sun, Ruobing Xie, et al.*2025 · 11 citations* 14. **[Union-of-Experts: Neurons in Mixture-of-Experts are Secretly Routers ↗](https://aclanthology.org/2026.acl-long.1675/) Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Songhao Wu et al.*2026* ## Co-authors here 12 of 16 co-authors with a page, the most papers together first. - [Jiaqi Zhu](https://md.research.elamur.ai/free/en/authors/jiaqi-zhu/) ×2 - [Shuaipeng Li](https://md.research.elamur.ai/free/en/authors/shuaipeng-li/) ×2 - [Xingwu Sun](https://md.research.elamur.ai/free/en/authors/xingwu-sun/) ×2 - [Zhen Yang](https://md.research.elamur.ai/free/en/authors/zhen-yang/) ×2 - [Chaofan Tao](https://md.research.elamur.ai/free/en/authors/chaofan-tao/) - [Chenming Shang](https://md.research.elamur.ai/free/en/authors/chenming-shang/) - [Di Wang](https://md.research.elamur.ai/free/en/authors/di-wang/) - [Hayden Kwok-Hay So](https://md.research.elamur.ai/free/en/authors/hayden-kwok-hay-so/) - [Hengyuan Zhang](https://md.research.elamur.ai/free/en/authors/hengyuan-zhang/) - [Jing Xiong](https://md.research.elamur.ai/free/en/authors/jing-xiong/) - [Kai Zhang](https://md.research.elamur.ai/free/en/authors/kai-zhang/) - [Naoaki Okazaki](https://md.research.elamur.ai/free/en/authors/naoaki-okazaki/) ## 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/) ×4: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/) ×3: [Proceedings of the AAAI Conference on Artificial Intelligence 2017](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/2017/) - International Joint Conference on Artificial Intelligence ×2 - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/) - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) - Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) ## Cited by Papers of our library cite their works 1,130 times (of the 149,439 papers whose bibliographies we read); [216 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/ruobing-xie/cited-by/). Updated 30 October 2026