🔗 Who cites «PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization»

95 papers of our library cite it (of the 149,439 whose bibliographies we read) · 24 with a page here, the most cited first · ← back to «PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization»

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. Unleashing the potential of prompt engineering for large language modelsarXiv:2310.14735 · Patterns 6(6) 101,260 (2025)Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.2023 · 536 citations
3. ChatDev: Communicative Agents for Software DevelopmentarXiv:2307.07924Chen Qian, Wei Liu, Hongzhang Liu, et al.2023 · 385 citations
4. Agent-Pro: Learning to Evolve via Policy-Level Reflection and OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Wenqi Zhang, Ke Tang, Hai Wu, et al.2024 · 52 citations
5. A Systematic Survey of Automatic Prompt Optimization TechniquesConference on Empirical Methods in Natural Language Processing (EMNLP)Kiran Ramnath, Kang Zhou, Sheng Guan, et al.2025 · 40 citations
6. Knowledge Boundary of Large Language Models: A SurveyAnnual Meeting of the Association for Computational Linguistics (ACL)Moxin Li, Yong Zhao, Wenxuan Zhang, et al.2025 · 30 citations
7. Large Language Models Can Solve Real-World Planning Rigorously with Formal Verification ToolsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yilun Hao, Yongchao Chen, Yang Zhang, et al.2025 · 18 citations
8. PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem SolvingConference on Empirical Methods in Natural Language Processing (EMNLP)Mihir Parmar, Xin Liu, Palash Goyal, et al.2025 · 16 citations
9. ReCreate: Reasoning and Creating Domain Agents Driven by ExperienceAnnual Meeting of the Association for Computational Linguistics (ACL)Zhezheng Hao, Hong Wang, Jian Luo, et al.2026 · 8 citations
10. ZERA: Zero-init Instruction Evolving Refinement Agent – From Zero Instructions to Structured Prompts via Principle-based OptimizationConference on Empirical Methods in Natural Language Processing (EMNLP)Seungyoun Yi, Minsoo Khang, Sungrae Park2025 · 5 citations
11. MAPRO: Recasting Multi-Agent Prompt Optimization as Maximum a Posteriori InferenceFindings of the Association for Computational LinguisticsZheyuan Zhang, Lin Ge, Hongjiang Li, et al.2026 · 3 citations
12. Rethinking Prompt Optimizers: From Prompt Merits to OptimizationConference of the European Chapter of the Association for Computational Linguistics (EACL)Zixiao Zhu, Hanzhang Zhou, Zijian Feng, et al.2026 · 3 citations
13. COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking ExplanationsFindings of the Association for Computational LinguisticsRui Xing, Preslav Nakov, Timothy Baldwin, et al.2026 · 2 citations
14. PromptLab: A Collaborative Platform for Prompt Engineering and Dataset CurationConference of the European Chapter of the Association for Computational Linguistics (EACL)Maged S. Al-shaibani, Zaid Alyafeai, Dania Refai, et al.2026 · 1 citation
15. ProxyPrompt: Securing System Prompts against Prompt Extraction AttacksFindings of the Association for Computational LinguisticsZhixiong Zhuang, Maria-Irina Nicolae, Hui-Po Wang, et al.2026 · 1 citation
16. AgentFactory: A Self-Evolving Framework Through Executable Subagent Accumulation and ReuseAnnual Meeting of the Association for Computational Linguistics (ACL)Zhang Zhang, Shuqi Lu, Hongjin Qian, et al.2026
17. Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based OptimizersConference of the European Chapter of the Association for Computational Linguistics (EACL)Andrew Zhao, Reshmi Ghosh, Vitor R. Carvalho, et al.2026
18. BayesFlow: A Probability Inference Framework for Meta-Agent Assisted Workflow GenerationFindings of the Association for Computational LinguisticsBo Yuan, Yun Zhou, Zhichao Xu, et al.2026
19. Neural at ArchEHR-QA 2026: One Method Fits All: Unified Prompt Optimization for Clinical QA over EHRsWorkshop on Patient-Oriented Language Processing @ LRECAbrar Majeedi, Viswanatha Reddy Gajjala, Sai Prasanna Teja Reddy Bogireddy, et al.2026
20. Optimizing RAG Rerankers with LLM Feedback via Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yuhang Wu, Xiangqing Shen, Fanfan Wang, et al.2026
21. PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMsFindings of the Association for Computational LinguisticsJiacheng Wang, Weiyan Zhang, Guangya Yu2026
22. Protecting Language Models Against Unauthorized Distillation through Trace RewritingAnnual Meeting of the Association for Computational Linguistics (ACL)Xinhang Ma, William Yeoh, Ning Zhang, et al.2026
23. Thesis Proposal: Intentional Inference for Insight GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Kristýna Onderková2026
24. Towards Self-Evolving Agents: Enabling Autonomy through Interactive Experience RefinementFindings of the Association for Computational LinguisticsCheng Yang, Xuemeng Yang, Licheng Wen, et al.2026

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