--- title: "Who cites Huan Zhao — 68 papers of our library" description: "68 papers of the Elamur Research library cite the works of Huan Zhao, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/huan-zhao/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/huan-zhao/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Huan Zhao](https://md.research.elamur.ai/free/en/authors/huan-zhao/) / cited by # Who cites Huan Zhao 70 citations of their works from 68 papers of our library (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← Huan Zhao](https://md.research.elamur.ai/free/en/authors/huan-zhao/) 1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations* 2. [**Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models arXiv:2304.01852 · Meta-Radiology (2023)100,017**Yiheng Liu, Tianle Han, Siyuan Ma, et al.*2023 · 940 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/) 3. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 520 citations* 4. **[ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 422 citations* 5. **[Large Language Models for Generative Information Extraction: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2023-large-language-models-generative-information/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Derong Xu, Wei Chen, Wenjun Peng, et al.*2023 · 406 citations* 6. **[Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yubo Ma, Yixin Cao, Yong Hong, et al.*2023 · 212 citations* 7. [**When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks arXiv:2311.08993**Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-context-learning-fall-short-why/) 8. **[Synergetic Event Understanding: A Collaborative Approach to Cross-Document Event Coreference Resolution with Large Language Models](https://md.research.elamur.ai/free/en/papers/min-2024-synergetic-event-understanding-collaborative-approach/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingkai Min, Qipeng Guo, Xiangkun Hu, et al.*2024 · 19 citations* 9. [**EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language Models arXiv:2402.11430**Jun Gao, Huan Zhao, Wei Wang, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-eventrl-enhancing-event-extraction-outcome/) 10. **[When Tasks Share Structure: A Comparative Study of Training Strategies for Generative Event Extraction](https://md.research.elamur.ai/free/en/papers/ravikumar-2026-when-tasks-share-structure-comparative/) [Workshop on Event Extraction and Understanding: Challenges and Applications](https://md.research.elamur.ai/free/en/venues/eeuca/)**Rishi Ravikumar, Riza Batista-Navarro*2026 · 1 citation* 11. **[EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain](https://md.research.elamur.ai/free/en/papers/lu-2026-exceeds-extracting-complex-events-nugget/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi-Fan Lu, Xian-Ling Mao, Bo Wang, et al.*2026* 12. **[GENOME: A New Geopolitical Event Methodology and Dataset using Large Language Models](https://md.research.elamur.ai/free/en/papers/orto-2026-genome-new-geopolitical-event-methodology/) [Workshop on Event Extraction and Understanding: Challenges and Applications](https://md.research.elamur.ai/free/en/venues/eeuca/)**Alessandro Dell'Orto, Jesse Kommandeur*2026* 13. **[MUC-4 Revisited: Document-level Event Analysis beyond Span-based Arguments](https://md.research.elamur.ai/free/en/papers/olsen-2026-muc-4-revisited-document-level/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Helene Bøsei Olsen, Erik Velldal, Lilja Øvrelid*2026* 55 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/huan-zhao/) — Huan Zhao