🧑‍🔬 Ziyue Qiao

🏛️ Affiliations

🎓Great Bay UniversityDongguan · China2024–2026 · 63 paperscurrent🔬Computer Network Information CenterBeijing · China2019–2025 · 16 papers🏛️Chinese Academy of SciencesBeijing · China2019–2025 · 13 papers🎓University of Chinese Academy of SciencesBeijing · China2020–2023 · 13 papersEducation🎓The Hong Kong University of Science and Technology (Guangzhou)Guangzhou · China2022–2024 · 11 papersEmployment · Postdoc🎓Hong Kong University of Science and TechnologyHong Kong · China2022–2024 · 7 papers🎓Dongguan University of TechnologyDongguan · China2026 · 2 papers🔬Guangzhou HKUST Fok Ying Tung Research InstituteGuangzhou · China2023 · 2 papers

🏛️School of Computing and Information Technology, Great Bay UniversityDongguan · China2024Employment since 2024

🏛️Computer Network Information Center Chinese Academy of SciencesHaidian District · ChinaEducation

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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. Large Language Model Agent: A Survey on Methodology, Applications and Challenges (2025 · 62 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…
2. Calibrating Inference Time Alignment with Sequence-level Risk Accumulation (2026)
   LLM defenses against jailbreaks often over-refuse. They block innocuous requests, such as how to "kill" a Linux process, because single tokens look dangerous. This paper presents SEAT, an inference-time decoding framework named for its approach of accumulating risk over whole sequences to calibrate alignment at test…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. Large Language Model Agent: A Survey on Methodology, Applications and ChallengesarXiv:2503.21460Junyu Luo, Weizhi Zhang, Ye Yuan, et al.2025 · 62 citations
2. Calibrating Inference Time Alignment with Sequence-level Risk AccumulationAnnual Meeting of the Association for Computational Linguistics (ACL)Shanwen Tan, Ziyang Dong, Wei Ju, et al.2026
3. DANCE: Diversity-attended Dynamic Caching with Asymmetric Quantization for Test-time Adaptation of Vision-Language Models ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetShunge Zou et al.2026

🤝 Co-authors here

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

• Bohan Wu
• Hao Wu
• Junwei Yang
• Junyu Luo
• Kun Wang
• Wei Ju
• Weizhi Zhang
• Xiao Luo
• Ye Yuan
• Yifan Wang
• Yiyang Gu
• Yusheng Zhao

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): ACL 2026
• Findings of the Association for Computational Linguistics: ACL 2026

🔗 Cited by

Papers of our library cite their works 57 times (of the 149,439 papers whose bibliographies we read); 16 citing papers with a page here →.

Updated 1 November 2026

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