---
title: "Who cites Shengran Hu — 199 papers of our library"
description: "199 papers of the Elamur Research library cite the works of Shengran Hu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/shengran-hu/cited-by/"
---
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# Who cites Shengran Hu

229 citations of their works from 199 papers of our library (of the 149,439 whose bibliographies we read) · 42 with a page here, the most cited first · [← Shengran Hu](https://md.research.elamur.ai/free/en/authors/shengran-hu/)

1. [**The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery arXiv:2408.06292**Chris Lu, Cong Lu, Robert Tjarko Lange, et al.*2024 · 372 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-ai-scientist-fully-automated/)
2. [**Agent Laboratory: Using LLM Agents as Research Assistants arXiv:2501.04227**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 139 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
3. [**Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models arXiv:2501.09686**Fengli Xu, Qianyue Hao, Zefang Zong, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-towards-large-reasoning-models-survey/)
4. [**AFlow: Automating Agentic Workflow Generation arXiv:2410.10762**Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-aflow-automating-agentic-workflow/)
5. [**Automated Design of Agentic Systems arXiv:2408.08435**Shengran Hu, Cong Lu, Jeff Clune*2024 · 89 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-automated-design-agentic-systems/)
6. [**CycleResearcher: Improving Automated Research via Automated Review arXiv:2411.00816**Yixuan Weng, Minjun Zhu, Guangsheng Bao, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/weng-2024-cycleresearcher-improving-automated-research/)
7. **[MasRouter: Learning to Route LLMs for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/yue-2025-masrouter-learning-route-llms-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanwei Yue, Guibin Zhang, Boyang Liu, et al.*2025 · 35 citations*
8. **[An AI system to help scientists write expert-level empirical software](https://md.research.elamur.ai/free/en/papers/aygun-2025-ai-system-help-scientists/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**Eser Aygün, Anastasiya Belyaeva, Gheorghe Comanici, et al.*2025 · 27 citations*
9. **[Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation](https://md.research.elamur.ai/free/en/papers/eger-2025-transforming-science-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Steffen Eger, Yong Cao, Jennifer D'Souza, et al.*2025 · 25 citations*
10. **[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*
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. **[AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents](https://md.research.elamur.ai/free/en/papers/tang-2026-autoagent-fully-automated-zero-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiabin Tang, Tianyu Fan, Chao Huang*2026 · 13 citations*
13. [**EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery arXiv:2603.08127**Yougang Lyu, Xi Zhang, Xinhao Yi, et al.*2026 · 10 citations*](https://md.research.elamur.ai/free/en/papers/lyu-2026-evoscientist-towards-multi-agent-evolving/)
14. **[ReCreate: Reasoning and Creating Domain Agents Driven by Experience](https://md.research.elamur.ai/free/en/papers/hao-2026-recreate-reasoning-creating-domain-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhezheng Hao, Hong Wang, Jian Luo, et al.*2026 · 8 citations*
15. **[EVOTOOL: Self-Evolving Tool-Use Policy Optimization in LLM Agents via Blame-Aware Mutation and Diversity-Aware Selection](https://md.research.elamur.ai/free/en/papers/yang-2026-evotool-self-evolving-tool-use/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuo Yang, Caren Han, Xueqi Ma, et al.*2026 · 6 citations*
16. [**AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model Discovery arXiv:2604.05550**Yu Li, Chenyang Shao, Xinyang Liu, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/li-2026-autosota-end-end-automated-research/)
17. **[Paper2Rebuttal: A Multi-Agent Framework for Transparent Author Response Assistance](https://md.research.elamur.ai/free/en/papers/ma-2026-paper2rebuttal-multi-agent-framework-transparent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianli Ma, Chang Guo, Zhiheng Tian, et al.*2026 · 5 citations*
18. **[MAPRO: Recasting Multi-Agent Prompt Optimization as Maximum a Posteriori Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-mapro-recasting-multi-agent-prompt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Zhang, Lin Ge, Hongjiang Li, et al.*2026 · 3 citations*
19. **[Self-Evolving Multi-Agent Systems via Textual Backpropagation](https://md.research.elamur.ai/free/en/papers/ma-2026-self-evolving-multi-agent-systems/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaowen Ma, Yunpu Ma, Chenyang Lin, et al.*2026 · 3 citations*
20. **[EvoRoute: Experience-Driven Self-Routing LLM Agent Systems](https://md.research.elamur.ai/free/en/papers/zhang-2026-evoroute-experience-driven-self-routing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guibin Zhang, Haiyang Yu, Kaiming Yang, et al.*2026 · 2 citations*
21. **[MedDCR: Learning to Design Agentic Workflows for Medical Coding](https://md.research.elamur.ai/free/en/papers/zheng-2026-meddcr-learning-design-agentic-workflows/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiyang Zheng, Islam Nassar, Thanh Vu, et al.*2026 · 2 citations*
22. **[AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists](https://md.research.elamur.ai/free/en/papers/pan-2026-airaxiv-ai-driven-open-access/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junshu Pan, Panzhong Lu, Yixuan Weng, et al.*2026 · 1 citation*
23. **[ComfyUI-R1: Exploring Reasoning Models for Workflow Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-comfyui-r1-exploring-reasoning-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenran Xu, Yiyu Wang, Xue Yang, et al.*2026 · 1 citation*
24. **[Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2026-easy-samples-are-all-you/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiyin Yu, Bo Zhang, Qibin Hou, et al.*2026 · 1 citation*
25. **[Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration](https://md.research.elamur.ai/free/en/papers/liu-2026-scaling-external-knowledge-input-beyond/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijun Liu, Zhennan Wan, Peng Li, et al.*2026 · 1 citation*
26. **[Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agent-gwo-collaborative-agents-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xudong Wang, Chaoning Zhang, Chenghao Li, et al.*2026*
27. **[AgentFactory: A Self-Evolving Framework Through Executable Subagent Accumulation and Reuse](https://md.research.elamur.ai/free/en/papers/zhang-2026-agentfactory-self-evolving-framework-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhang Zhang, Shuqi Lu, Hongjin Qian, et al.*2026*
28. **[Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers](https://md.research.elamur.ai/free/en/papers/zhao-2026-are-my-optimized-prompts-compromised/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Andrew Zhao, Reshmi Ghosh, Vitor R. Carvalho, et al.*2026*
29. **[Attribution-Based Analysis and Optimization of Modular Agentic Workflows](https://md.research.elamur.ai/free/en/papers/yang-2026-attribution-based-analysis-optimization-modular/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingxuan Yang, Bo Huang, Siyuan Qi, et al.*2026*
30. **[BayesFlow: A Probability Inference Framework for Meta-Agent Assisted Workflow Generation](https://md.research.elamur.ai/free/en/papers/yuan-2026-bayesflow-probability-inference-framework-meta/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bo Yuan, Yun Zhou, Zhichao Xu, et al.*2026*
31. **[ComfyFlow: Benchmarking LLMs for AIGC Workflow Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-comfyflow-benchmarking-llms-aigc-workflow/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenran Xu, Yiyu Wang, Yunxin Li, et al.*2026*
32. **[Do We Always Need Query-Level Workflows? Rethinking Agentic Workflow Generation for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/wang-2026-do-we-always-need-query/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zixu Wang, Bingbing Xu, Yige Yuan, et al.*2026*
33. **[EvoSci: A Bio-Inspired Multi-Agent Framework for the Evolution of Scientific Discovery](https://md.research.elamur.ai/free/en/papers/xiong-2026-evosci-bio-inspired-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyu Xiong, Yuqi Ren, Deyi Xiong*2026*
34. **[FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in Lean](https://md.research.elamur.ai/free/en/papers/meadows-2026-formalscience-scalable-human-loop-autoformalisation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jordan Meadows, Lan Zhang, Andre Freitas*2026*
35. **[FusionFlow: Enabling Deep Structural Exploration for Automated Agentic Workflow Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-fusionflow-enabling-deep-structural-exploration/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiang Wang, Zongtao Yang, Zhuojian Hong, et al.*2026*
36. **[GALA: Geometric Data Selection with Strategic Prospecting for Large Language Model Self-training](https://md.research.elamur.ai/free/en/papers/xie-2026-gala-geometric-data-selection-strategic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhongwei Xie, Ruihao Liao, Zimo Wang, et al.*2026*
37. **[Grammar Search for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/singh-2026-grammar-search-multi-agent-systems/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mayank Singh, Vikas Yadav, Shiva Krishna Reddy Malay, et al.*2026*
38. **[Hetero-Designer: Automated Design of Multi-Agent Systems with Heterogeneous LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-hetero-designer-automated-design-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiheng Zhang, Yuanzhe Zhang, Bohan Yu, et al.*2026*
39. **[Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement](https://md.research.elamur.ai/free/en/papers/ying-2026-multi-agent-procedural-graph-extraction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wangyang Ying, Yanchi Liu, Xujiang Zhao, et al.*2026*
40. **[NeuralFSM: Adaptive Multi-Agent Coordination via Learning Finite-State Execution Policy](https://md.research.elamur.ai/free/en/papers/wang-2026-neuralfsm-adaptive-multi-agent-coordination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiye Wang, Yu Wang, Jianbin Li, et al.*2026*
41. **[Pushing the Frontiers of Scientific Fact-Checking: The SCINLP Dataset](https://md.research.elamur.ai/free/en/papers/maab-2026-pushing-frontiers-scientific-fact-checking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Iffat Maab, Junichi Yamagishi*2026*
42. **[Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation](https://md.research.elamur.ai/free/en/papers/mule-2026-teaching-language-models-forecast-research/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Srujan P Mule, Aniketh Garikaparthi, Manasi Patwardhan*2026*

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

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