Fetching the paper…
Reading the bibliography…
While large language models (LLMs) have recently demonstrated strong potential in solving planning problems, there is a trade-off between flexibility and complexity.
On the complexity of blocks-world planning
Naresh Gupta and Dana S Nau · 1992
Earlier work this paper cites.
Pddl— the planning domain definition language
Constructions Aeronautiques, Adele Howe, Craig Knoblock, ISI Drew McDermott, Ashwin Ram, Manuela Veloso, Daniel Weld, David Wilkins Sri, Anthony Barrett, Dave Christianson, et al · 1998
Earlier work this paper cites.
Z3: An efficient smt solver
Leonardo De Moura and Nikolaj Bjørner · 2008
Earlier work this paper cites.
An introduction to the planning domain definition language , volume 13
Patrik Haslum, Nir Lipovetzky, Daniele Magazzeni, Christian Muise, Ronald Brachman, Francesca Rossi, and Peter Stone · 2019
Earlier work this paper cites.
Do as i can, not as i say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, et al · 2022
Earlier work this paper cites.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
Earlier work this paper cites.
Large language models still can’t plan (a benchmark for llms on planning and reasoning about change)
Karthik Valmeekam, Alberto Olmo, Sarath Sreedharan, and Subbarao Kambhampati · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Earlier work this paper cites.
Autoformalization with large language models
Yuhuai Wu, Albert Qiaochu Jiang, Wenda Li, Markus Rabe, Charles Staats, Mateja Jamnik, and Christian Szegedy · 2022
Earlier work this paper cites.
React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2022
Earlier work this paper cites.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Earlier work this paper cites.
Autotamp: Autoregressive task and motion planning with llms as translators and checkers
Yongchao Chen, Jacob Arkin, Yang Zhang, Nicholas Roy, and Chuchu Fan · 2023
Earlier work this paper cites.
Leveraging pre-trained large language models to construct and utilize world models for model-based task planning
Lin Guan, Karthik Valmeekam, Sarath Sreedharan, and Subbarao Kambhampati · 2023
Earlier work this paper cites.
Solving math word problems by combining language models with symbolic solvers
Joy He-Yueya, Gabriel Poesia, Rose E Wang, and Noah D Goodman · 2023
Cited alongside, same era.
Large language models for supply chain optimization
Beibin Li, Konstantina Mellou, Bo Zhang, Jeevan Pathuri, and Ishai Menache · 2023
Cited alongside, same era.
Llm+ p: Empowering large language models with optimal planning proficiency
Bo Liu, Yuqian Jiang, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, and Peter Stone · 2023
Cited alongside, same era.
Logic-lm: Empowering large language models with symbolic solvers for faithful logical reasoning
Liangming Pan, Alon Albalak, Xinyi Wang, and William Yang Wang · 2023
Cited alongside, same era.
Yongchao Chen, Jacob Arkin, Yilun Hao, Yang Zhang, Nicholas Roy, and Chuchu Fan · 2024
Closest in time.
Robust planning with llm-modulo framework: Case study in travel planning
Atharva Gundawar, Mudit Verma, Lin Guan, Karthik Valmeekam, Siddhant Bhambri, and Subbarao Kambhampati · 2024
Closest in time.
Large language models can plan your travels rigorously with formal verification tools
Yilun Hao, Yongchao Chen, Yang Zhang, and Chuchu Fan · 2024
Closest in time.
Llms can’t plan, but can help planning in llm-modulo frameworks
Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, Kaya Stechly, Mudit Verma, Siddhant Bhambri, Lucas Saldyt, and Anil Murthy · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, et al · 2023
Cited alongside, same era.
Llm-planner: Few-shot grounded planning for embodied agents with large language models
Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M Sadler, Wei-Lun Chao, and Yu Su · 2023
Cited alongside, same era.
Autoplanbench:: Automatically generating benchmarks for llm planners from pddl
Katharina Stein and Alexander Koller · 2023
Cited alongside, same era.
On the planning abilities of large language models-a critical investigation
Karthik Valmeekam, Matthew Marquez, Sarath Sreedharan, and Subbarao Kambhampati · 2023
Cited alongside, same era.
Translating natural language to planning goals with large-language models
Yaqi Xie, Chen Yu, Tongyao Zhu, Jinbin Bai, Ze Gong, and Harold Soh · 2023
Cited alongside, same era.
https://www.anthropic.com/news/claude-3-5-sonnet
Claude 3.5 sonnet · 2024
Cited alongside, same era.
https://openai.com/index/hello-gpt-4o/
Hello gpt-4o · 2024
Cited alongside, same era.
https://openai.com/index/introducing-openai-o1-preview/
Introducing openai o1-preview · 2024
Cited alongside, same era.
Zelong Li, Wenyue Hua, Hao Wang, He Zhu, and Yongfeng Zhang · 2024
Closest in time.
Kumar Manas, Stefan Zwicklbauer, and Adrian Paschke · 2024
Closest in time.
Cape: Corrective actions from precondition errors using large language models
Shreyas Sundara Raman, Vanya Cohen, Ifrah Idrees, Eric Rosen, Raymond Mooney, Stefanie Tellex, and David Paulius · 2024
Closest in time.
Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom · 2024
Closest in time.
Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change
Karthik Valmeekam, Matthew Marquez, Alberto Olmo, Sarath Sreedharan, and Subbarao Kambhampati · 2024
Closest in time.
Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan · 2024
Closest in time.
Satlm: Satisfiability-aided language models using declarative prompting
Xi Ye, Qiaochu Chen, Isil Dillig, and Greg Durrett · 2024
Closest in time.
Isr-llm: Iterative self-refined large language model for long-horizon sequential task planning
Zhehua Zhou, Jiayang Song, Kunpeng Yao, Zhan Shu, and Lei Ma · 2024
Closest in time.