🧑‍🔬 Shu Yang

🏛️ Affiliations

🏥Jiangsu Province HospitalNanjing · China2024–2026 · 2 paperscurrent🎓King Abdullah University of Science and TechnologyJeddah · Saudi Arabia2025–2026 · 2 paperscurrent🎓Nanjing Medical UniversityNanjing · China2026 · 2 paperscurrent🏥The Affiliated Taizhou People's Hospital of Nanjing Medical UniversityTaizhou · China2026 · 2 paperscurrent🎓Tsinghua UniversityBeijing · China2014–2025 · 11 papersEmployment 2022–2025 · Postdoctoral Researcher, Department of Electronic Engineering🎓Beijing Institute of TechnologyBeijing · China2015–2025 · 9 papersEmployment 2015–2021 · PHD studentEmployment since 2025 · Assistant Professor, College of education🎓Shenyang Normal UniversityShenyang · China2008–2011 · 7 papers🎓Beijing Normal UniversityBeijing · China2012–2016 · 6 papers🔬State Key Laboratory of Earth Surface Processes and Resource EcologyBeijing2012–2016 · 6 papers🎓Shenzhen UniversityShenzhen · China2018–2025 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 11 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

📄 Papers

The most cited first (OpenAlex and our library).

1. A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions (2025 · 277 citations)
   Text from LLMs such as GPT-4, Claude and PaLM now reads so much like human writing that people spot it only slightly better than chance.
2. Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScore (2025 · 17 citations)
   Detectors for machine-generated text usually need large labeled training sets (supervised classifiers) or access to the generating model's logits (white-box zero-shot methods such as DetectGPT or Fast-DetectGPT).
3. Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMs (2026 · 6 citations)
   Video-LLMs often give up on what they actually see in a video when a user pushes a wrong answer. This behaviour is called sycophancy. It has been studied for text LLMs and, to a lesser degree, for image models, but no systematic test existed for video. The authors built ViSE, a benchmark of multiple-choice questions…
4. AutoMonitor-Bench: Evaluating the Reliability of LLM-Based Misbehavior Monitor (2026 · 2 citations)
   LLMs are increasingly used to check other models' outputs and reasoning traces for misbehavior, but it is unclear how reliable these monitors are.
5. Understanding and Mitigating Political Stance Cross-topic Generalization in Large Language Models (2026 · 1 citation)
   Fine-tuning a large language model on one political topic can shift its stance on unrelated topics as well.

All works

6 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

1. A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future DirectionsComputational LinguisticsJunchao Wu, Shu Yang, Runzhe Zhan, et al.2025 · 277 citations
2. Transferable Curriculum for Weakly-Supervised Domain Adaptation ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetShu Yang et al.2019 · 106 citations
3. Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScoreInternational Conference on Computational Linguistics (COLING)Junchao Wu, Runzhe Zhan, Derek F. Wong, et al.2025 · 17 citations
4. Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Wenrui Zhou, Mohamed Hendy, Shu Yang, et al.2026 · 6 citations
5. AutoMonitor-Bench: Evaluating the Reliability of LLM-Based Misbehavior MonitorFindings of the Association for Computational LinguisticsShu Yang, Jingyu Hu, Tong Li, et al.2026 · 2 citations
6. Understanding and Mitigating Political Stance Cross-topic Generalization in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jiayi Zhang, Shu Yang, Junchao Wu, et al.2026 · 1 citation

🤝 Co-authors here

12 of 14 co-authors with a page, the most papers together first.

• Derek F. Wong ×3
• Di Wang ×3
• Junchao Wu ×3
• Lidia S. Chao ×2
• Runzhe Zhan ×2
• Hanqi Yan
• Jiayi Zhang
• Lijie Hu
• Min Zhang
• Tong Li
• Wenxuan Wang
• Xuebo Liu

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 ×2
• Computational Linguistics: Computational Linguistics 2025
• International Conference on Computational Linguistics (COLING): COLING 2025
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
• Proceedings of the AAAI Conference on Artificial Intelligence

🔗 Cited by

Papers of our library cite their works 99 times (of the 149,439 papers whose bibliographies we read); 29 citing papers with a page here →.

Updated 31 October 2026

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