🧑‍🔬 Ruobing Xie

🏛️ Affiliations

🏢TencentShenzhen · China2017–2026 · 148 papersEmployment since 2017 · Senior Researchercurrent🎓Tsinghua UniversityBeijing · China2010–2024 · 11 papersEducation 2010–2017🔬State Key Laboratory of Intelligent Technology and SystemsBeijing · China2016–2017 · 6 papers🏛️Chinese Academy of SciencesBeijing · China2023–2024 · 2 papers🔬Institute of Computing TechnologyBeijing · China2023–2024 · 2 papers

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.

📅 Works by year

2020s

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence (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 (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 (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 (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 ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetRuobing Xie et al.2016 · 776 citations
2. Iterative Entity Alignment via Joint Knowledge Embeddings ↗International Joint Conference on Artificial Intelligence · no summary yetHao Zhu et al.2017 · 407 citations
3. Large Language Models are Zero-Shot Rankers for Recommender Systems ↗arXiv:2305.08845 · no summary yetYupeng Hou et al.2023 · 394 citations
4. Image-embodied Knowledge Representation Learning ↗International Joint Conference on Artificial Intelligence · no summary yetRuobing Xie et al.2017 · 298 citations
5. Improved Word Representation Learning with Sememes ↗Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetYilin Niu et al.2017 · 140 citations
6. Advancing LLM Reasoning Generalists with Preference Trees ↗arXiv:2404.02078 · no summary yetLifan Yuan et al.2024 · 94 citations
7. Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with ConfidenceProceedings of the AAAI Conference on Artificial IntelligenceRuobing Xie, Zhiyuan Liu, Fen Lin, et al.2017 · 93 citations
8. Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised Data ↗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 yetRuidong Wu et al.2019 · 84 citations
9. Hierarchical Reinforcement Learning for Integrated Recommendation ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetRuobing Xie et al.2021 · 79 citations
10. Connecting Embeddings for Knowledge Graph Entity Typing ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetYu Zhao et al.2020 · 67 citations
11. Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by TencentarXiv:2411.02265Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.2024 · 25 citations
12. Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher DistillationAnnual Meeting of the Association for Computational Linguistics (ACL)Hengyuan Zhang, Shiping Yang, Xiao Liang, et al.2026 · 13 citations
13. HMoE: Heterogeneous Mixture of Experts for Language ModelingConference on Empirical Methods in Natural Language Processing (EMNLP)An Wang, Xingwu Sun, Ruobing Xie, et al.2025 · 11 citations
14. Union-of-Experts: Neurons in Mixture-of-Experts are Secretly Routers ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetSonghao Wu et al.2026

🤝 Co-authors here

12 of 16 co-authors with a page, the most papers together first.

• Jiaqi Zhu ×2
• Shuaipeng Li ×2
• Xingwu Sun ×2
• Zhen Yang ×2
• Chaofan Tao
• Chenming Shang
• Di Wang
• Hayden Kwok-Hay So
• Hengyuan Zhang
• Jing Xiong
• Kai Zhang
• 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) ×4: ACL 2026
• Proceedings of the AAAI Conference on Artificial Intelligence ×3: 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): EMNLP 2025
• Findings of the Association for Computational Linguistics
• 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 →.

Updated 30 October 2026

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