Yusheng Zhao
Yusheng Zhao has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining; often with Jian Zhao, Junyu Luo.
OpenAlex · ORCID · h-index 78 · 551 works · 23,802 citations OpenAlex, 2026-10-14
📄 2 works in our library · 🔗 Cited 54 times in our library · ⭐ Paper Stars ranking: #5330
Affiliations
🎓Eastern Institute of Technology, NingboNingbo2023–2026 · 24 papers🎓Eastern Institute of TechnologyNapier City ·
New Zealand2024–2026 · 7 papers🎓University of Science and Technology of ChinaHefei ·
China2024–2026 · 3 papers🎓Tianjin University of TechnologyTianjin ·
China2026 · 2 papers🔬Los Alamos National LaboratoryLos Alamos ·
United States1995–2020 · 174 papers🎓Southern University of Science and TechnologyShenzhen ·
China2016–2025 · 153 papers🎓University of Nevada, Las VegasLas Vegas ·
United States2007–2018 · 94 papers🏢Los Alamos National SecurityLos Alamos ·
United States2000–2014 · 22 papers🏛️Chinese Academy of SciencesBeijing ·
China2013–2023 · 14 papers🔬Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)Guangzhou ·
China2021–2023 · 14 papers
Concepts, shelves and topics
📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksComputer Vision and Pattern Recognition · 1 workHardware and Architecture · 1 work
🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work
Works by year
2020s
Papers
- Large Language Model Agent: A Survey on Methodology, Applications and Challenges (2025 · 59 citations)
Work on LLM-based agents has grown quickly but remains scattered. Existing reviews tend to cover one slice, such as games, deployment settings, multimodality or security, or they give broad overviews without a method-level breakdown. Luo et al. address this with a survey built around how agents are engineered. Its… - The Mark Fades: Adaptive Evolutionary Paraphrase-based Attack against LLM Watermarks (2026)
The paper looks at how fragile statistical watermarks in LLM-generated text are when an attacker can only rewrite the text. Existing paraphrase attacks force a trade-off: light rewriting leaves the watermark detectable, while heavy rewriting damages meaning and fluency.
Co-authors here
Venues
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
Cited by
Updated
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