🧑‍🔬 Tao Fan

🏛️ Affiliations

🎓Nanjing University of Finance and EconomicsNanjing · China2024–2026 · 10 papersEmployment since 2024 · Lecturer, School of Public Administrationcurrent🎓Hong Kong University of Science and TechnologyHong Kong · China2026 · 4 paperscurrent🎓Nanjing UniversityNanjing · China2020–2026 · 1 paperEducation 2020–2024 · Ph.D., School of Information Managementcurrent🎓University of BernBern · Switzerland2022–2023Education 2022–2023 · Visiting Ph.D. student, Digital Humanities🎓Nanjing University of Science and TechnologyNanjing · China2017–2020Education 2017–2020 · Master, School of Economics and Management

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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. FedMKT: Federated Mutual Knowledge Transfer for Large and Small Language Models (2025 · 10 citations)
   Federated work on LLMs has mostly followed two separate tracks. In one, clients jointly fine-tune identical LLMs. In the other, a server-side LLM teaches small language models (SLMs) on clients. Neither improves the server LLM and the client SLMs together. FedMKT, a parameter-efficient framework, makes knowledge flow…
2. When More Thinking Hurts: Overthinking in LLM Test-Time Compute Scaling (2026 · 2 citations)
   Test-time scaling research usually assumes that longer reasoning always gives better answers. This paper tests that assumption directly. It measures how much each extra 500 reasoning tokens adds to accuracy. Two open-weight 32B models, DeepSeek-R1-32B and s1-32B, are run under budget forcing at 32 budgets from 500 to…
3. InferenceDynamics: Adaptive LLM Routing through Structured Capability and Knowledge Profiling (2026 · 1 citation)
   Choosing which large language model should answer a given query becomes difficult as the number of specialized models grows.

All works

6 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. FedMKT: Federated Mutual Knowledge Transfer for Large and Small Language ModelsInternational Conference on Computational Linguistics (COLING)Tao Fan, Guoqiang Ma, Yan Kang, et al.2025 · 10 citations
2. When More Thinking Hurts: Overthinking in LLM Test-Time Compute ScalingFindings of the Association for Computational LinguisticsShu Zhou, Rui Ling, Junan Chen, et al.2026 · 2 citations
3. InferenceDynamics: Adaptive LLM Routing through Structured Capability and Knowledge ProfilingAnnual Meeting of the Association for Computational Linguistics (ACL)Haochen Shi, Tianshi Zheng, Weiqi Wang, et al.2026 · 1 citation
4. MTO: A Multi-turn Conversational Text-to-OverpassQL Dataset for Enhanced OpenStreetMap Query Generation ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetHaodi Zhang et al.2026
5. DynamicFocalPO: Adaptive Focusing Strategy for Preference Optimization ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetShu Zhou et al.2026
6. The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAG ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetShu Zhou et al.2026

🤝 Co-authors here

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

• Baixuan Xu
• Chunkit Chan
• Chunyang Li
• Hao Wang
• Kai Chen
• Qiang Yang
• Rui Ling
• Tianshi Zheng
• Weiqi Wang
• Xin Wang
• Yangqiu Song
• Yuanfeng Song

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) ×2: ACL 2026
• Findings of the Association for Computational Linguistics: ACL 2026 ×2
• International Conference on Computational Linguistics (COLING): COLING 2025
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026

🔗 Cited by

Papers of our library cite their works 9 times (of the 149,439 papers whose bibliographies we read).

Updated 31 October 2026

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