Who cites «The Fast Downward Planning System»
- ProgPrompt: Generating Situated Robot Task Plans using Large Language ModelsarXiv:2209.11302Ishika Singh, Valts Blukis, Arsalan Mousavian, et al.2022 · 735 citations
- ALFWorld: Aligning Text and Embodied Environments for Interactive LearningarXiv:2010.03768Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, et al.2020 · 322 citations
- PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about ChangeConference on Neural Information Processing Systems (NeurIPS)Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.2022 · 222 citations
- LLM+P: Empowering Large Language Models with Optimal Planning ProficiencyarXiv:2304.11477Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.2023 · 216 citations
- Large Language Models as Commonsense Knowledge for Large-Scale Task PlanningConference on Neural Information Processing Systems (NeurIPS)Zirui Zhao, Wee Sun Lee, David Hsu2023 · 153 citations
- Many-Shot In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.2024 · 142 citations
- Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task PlanningConference on Neural Information Processing Systems (NeurIPS)Lin Guan, Karthik Valmeekam, Sarath Sreedharan, et al.2023 · 115 citations
- Generalized Planning in PDDL Domains with Pretrained Large Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceTom Silver, Soham Dan, Kavitha Srinivas, et al.2023 · 112 citations
- PlanGenLLMs: A Modern Survey of LLM Planning CapabilitiesAnnual Meeting of the Association for Computational Linguistics (ACL)Hui Wei, Zihao Zhang, Shenghua He, et al.2025 · 55 citations
- SayCanPay: Heuristic Planning with Large Language Models using Learnable Domain KnowledgeProceedings of the AAAI Conference on Artificial IntelligenceRishi Hazra, Pedro Zuidberg Dos Martires, Luc De Raedt2023 · 51 citations
- 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
- Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Raffaele Pisano, Roberto Navigli2026 · 1 citation
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