🧑‍🔬 Yiyuan Yang

🏛️ Affiliations

🎓University of OxfordOxford · United Kingdom2023–2026 · 13 paperscurrent🏥First Affiliated Hospital of Xi'an Jiaotong UniversityXi'an · China2020–2026 · 4 paperscurrent🎓Tsinghua UniversityBeijing · China2020–2024 · 8 papers🎓University of South ChinaHengyang · China2019–2022 · 7 papers🎓Tsinghua Shenzhen International Graduate SchoolShenzhen · China2020–2021 · 4 papers🎓Beihang UniversityBeijing · China2018–2019 · 4 papers🏥First Hospital of Xi'anXi'an · China2020–2024 · 3 papers🎓University of Technology SydneySydney · Australia2024–2025 · 2 papers🎓Liupanshui Normal UniversityLiupanshui · China2023–2024 · 2 papers🎓Vanderbilt UniversityNashville · United States2020–2021 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 8 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. Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement (2025 · 21 citations)
   Most time series research targets one numerical task at a time, such as forecasting or anomaly detection. There is also little data that pairs natural language with time series, which holds back models able to discuss and reason about temporal data. The authors propose Time-MQA, a framework that treats several time…
2. Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback (2026 · 3 citations)
   Conventional time series anomaly detection (TSAD) usually just labels data as normal or anomalous. It does not say what kind of anomaly occurred or why. The authors propose TIME-RA, which recasts TSAD as a generative reasoning problem. A (multimodal) LLM must detect an anomaly, assign it to a fine-grained category…

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. DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection ↗ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · no summary yetYiyuan Yang et al.2023 · 358 citations
2. Time-MQA: Time Series Multi-Task Question Answering with Context EnhancementAnnual Meeting of the Association for Computational Linguistics (ACL)Yaxuan Kong, Yiyuan Yang, Yoontae Hwang, et al.2025 · 21 citations
3. Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM FeedbackFindings of the Association for Computational LinguisticsYiyuan Yang, Zichuan Liu, Lei Song, et al.2026 · 3 citations

🤝 Co-authors here

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

• Qingsong Wen ×2
• Jiang Bian
• Ming Jin
• Stephen Wang
• Zhangyang Wang

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 2025
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
• ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

🔗 Cited by

Papers of our library cite their works 16 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated 2 November 2026

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/yiyuan-yang/