---
title: "Who cites Xiang Zhuang — 74 papers of our library"
description: "74 papers of the Elamur Research library cite the works of Xiang Zhuang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/xiang-zhuang/cited-by/"
---
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# Who cites Xiang Zhuang

77 citations of their works from 74 papers of our library (of the 149,439 whose bibliographies we read) · 31 with a page here, the most cited first · [← Xiang Zhuang](https://md.research.elamur.ai/free/en/authors/xiang-zhuang/)

1. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
2. **[Scientific Large Language Models: A Survey on Biological & Chemical Domains](https://md.research.elamur.ai/free/en/papers/zhang-2024-scientific-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Qiang Zhang, Keyang Ding, Tianwen Lyv, et al.*2024 · 154 citations*
3. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
4. [**Self-Distillation Enables Continual Learning arXiv:2601.19897**Idan Shenfeld, Mehul Damani, Jonas Hubotter, et al.*2026 · 62 citations*](https://md.research.elamur.ai/free/en/papers/shenfeld-2026-self-distillation-enables-continual-learning/)
5. [**RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts arXiv:2411.15114**Hjalmar Wijk, Tao Lin, Joel Becker, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/wijk-2024-re-bench-evaluating-frontier/)
6. **[From Automation to Autonomy: A Survey on Large Language Models in Scientific Discovery](https://md.research.elamur.ai/free/en/papers/zheng-2025-automation-autonomy-survey-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianshi Zheng, Zheye Deng, Hong Ting Tsang, et al.*2025 · 39 citations*
7. **[SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature](https://md.research.elamur.ai/free/en/papers/wadden-2025-sciriff-resource-enhance-language-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**David Wadden, Kejian Shi, Jacob Morrison, et al.*2025 · 27 citations*
8. [**Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents arXiv:2503.24047**Shuo Ren, Can Xie, Pu Jian, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/ren-2025-scientific-intelligence-survey-llm/)
9. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
10. [**From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery arXiv:2508.14111**Jiaqi Wei, Yuejin Yang, Xiang Zhang, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/wei-2025-ai-science-agentic-science/)
11. [**ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning arXiv:2501.06590**Xiangru Tang, Tianyu Hu, Muyang Ye, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/tang-2025-chemagent-self-updating-library-large/)
12. [**Training a Scientific Reasoning Model for Chemistry arXiv:2506.17238**Siddharth M. Narayanan, James D. Braza, Ryan-Rhys Griffiths, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/narayanan-2025-training-scientific-reasoning-model/)
13. [**OmniScience: A Domain-Specialized LLM for Scientific Reasoning and Discovery arXiv:2503.17604**Vignesh Prabhakar, Md Amirul Islam, Adam Atanas, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/prabhakar-2025-omniscience-domain-specialized-llm-scientific/)
14. [**KL for a KL: On-Policy Distillation with Control Variate Baseline arXiv:2605.07865**Minjae Oh, Sangjun Song, Gyubin Choi, et al.*2026 · 8 citations*](https://md.research.elamur.ai/free/en/papers/oh-2026-kl-kl-policy-distillation-control/)
15. [**SafeScientist: Toward Risk-Aware Scientific Discoveries by LLM Agents arXiv:2505.23559**Kunlun Zhu, Jiaxun Zhang, Ziheng Qi, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-safescientist-toward-risk-aware-scientific/)
16. **[A Survey of Large Language Models for Text-Guided Molecular Discovery: From Molecule Generation to Optimization](https://md.research.elamur.ai/free/en/papers/wang-2026-survey-large-language-models-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqing Wang, Kexin Zhang, Zihan Zhao, et al.*2026 · 7 citations*
17. [**A Survey of AI Scientists arXiv:2510.23045**Guiyao Tie, Pan Zhou, Lichao Sun*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/tie-2025-survey-ai-scientists/)
18. **[Instructions are all you need: Self-supervised Reinforcement Learning for Instruction Following](https://md.research.elamur.ai/free/en/papers/ren-2026-instructions-are-all-you-need/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingyu Ren, Qianyu He, Powei Chang, et al.*2026 · 3 citations*
19. [**Large Means Left: Political Bias in Large Language Models Increases with Their Number of Parameters arXiv:2505.04393**David Exler, Mark Schutera, Markus Reischl, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/exler-2025-large-means-left-political-bias/)
20. [**PseudoBench: Measuring How Agentic Auto-Research Fuels Pseudoscience arXiv:2606.18060**Xinyang Liao, Lingyu Li, Huacan Liu, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/liao-2026-pseudobench-measuring-agentic-auto/)
21. [**Workflow Closure Is Not Scientific Closure in Auto-Research Systems arXiv:2605.26200**Shuai Wang, Xinyuan Tian, Pangpang Liu, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/wang-2026-workflow-closure-scientific-closure/)
22. [**Auditing Discovery Claims: A Two-Sided Criterion for Agentic Science, with the Negative Side Decidable arXiv:2608.00981**Wenhui Chen, Jianlin Chen, Ziyao Lin, et al.*2026*](https://md.research.elamur.ai/free/en/papers/chen-2026-auditing-discovery-claims-two/)
23. **[ChemVLR: Prioritizing Reasoning in Perception for Chemical Vision-Language Understanding](https://md.research.elamur.ai/free/en/papers/zhao-2026-chemvlr-prioritizing-reasoning-perception-chemical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuanle Zhao, Xinyuan Cai, Xiang Cheng, et al.*2026*
24. **[ClimAgent: LLM as Agents for Autonomous Open-ended Climate Science Analysis](https://md.research.elamur.ai/free/en/papers/wang-2026-climagent-llm-as-agents-autonomous/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Wang, Jindong Han, Wei Fan, et al.*2026*
25. **[Datasets for Scientific Literature Understanding: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2026-datasets-scientific-literature-understanding-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanzhe Zhang, Xun Zhao, Maodi Hu, et al.*2026*
26. **[JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-judgeagent-beyond-static-benchmarks-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichao Shi, Xuhui Jiang, Chengjin Xu, et al.*2026*
27. **[KGRxn-LLM: Knowledge Graph Enhanced Large Language Models for Molecular Reaction Reasoning](https://md.research.elamur.ai/free/en/papers/liu-2026-kgrxn-llm-knowledge-graph-enhanced/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Weichen Liu, Qiyao Xue, Yuyang Wu, et al.*2026*
28. **[LLMs Know More About Numbers than They Can Say](https://md.research.elamur.ai/free/en/papers/yuchi-2026-llms-know-more-about-numbers/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Fengting Yuchi, Li Du, Jason Eisner*2026*
29. **[MDC-Bench: A Multidisciplinary Causal Benchmark Based on Causal Structures for Evaluating Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-mdc-bench-multidisciplinary-causal-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peng Wang, Yuxiong Yan, Xiao Ding, et al.*2026*
30. [**Position: Academic Conferences are Potentially Facing Denominator Gaming Caused by Fully Automated Scientific Agents arXiv:2605.09915**Rong Shan, Te Gao, Hang Zheng, et al.*2026*](https://md.research.elamur.ai/free/en/papers/shan-2026-position-academic-conferences-potentially/)
31. **[WildSci: Advancing Scientific Reasoning from In-the-Wild Literature](https://md.research.elamur.ai/free/en/papers/liu-2026-wildsci-advancing-scientific-reasoning-wild/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengxiao Liu, Deepak Nathani, Zekun Li, et al.*2026*

43 more citing papers of our library have no page here yet.

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