Fetching the paper…
Reading the bibliography…
Among the most important properties of algorithms investigated in computer science are soundness, completeness, and complexity.
A formal basis for the heuristic determination of minimum cost paths
Peter E. Hart et al · 1968
Earlier work this paper cites.
Introduction to Algorithms
Thomas H. Cormen, Charles E. Leiserson, and Ronald L. Rivest · 1990
Earlier work this paper cites.
The Fast Downward planning system
Malte Helmert · 2006
Earlier work this paper cites.
Plansformer: Generating symbolic plans using transformers
Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Lior Horesh, Biplav Srivastava, Francesco Fabiano, and Andrea Loreggia · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou · 2022
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.
Reasoning with language model is planning with world model
Shibo Hao, Yi Gu, Haodi Ma, Joshua Hong, Zhen Wang, Daisy Wang, and Zhiting Hu · 2023
Earlier work this paper cites.
Algorithm of thoughts: Enhancing exploration of ideas in large language models
Bilgehan Sel, Ahmad Al-Tawaha, Vanshaj Khattar, Lu Wang, Ruoxi Jia, and Ming Jin · 2023
Cited alongside, same era.
Reflexion: language agents with verbal reinforcement learning
Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao · 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.
ReWOO: Decoupling reasoning from observations for efficient augmented language models
Binfeng Xu, Zhiyuan Peng, Bowen Lei, Subhabrata Mukherjee, Yuchen Liu, and Dongkuan Xu · 2023
Cited alongside, same era.
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 · 2023
Graph of thoughts: Solving elaborate problems with large language models
Maciej Besta, Nils Blach, Ales Kubicek, Robert Gerstenberger, Michal Podstawski, Lukas Gianinazzi, Joanna Gajda, Tomasz Lehmann, Hubert Niewiadomski, Piotr Nyczyk, and Torsten Hoefler · 2024
Closest in time.
Stream of Search (SoS): Learning to search in language
Kanishk Gandhi, Denise Lee, Gabriel Grand, Muxin Liu, Winson Cheng, Archit Sharma, and Noah D. Goodman · 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.
GPT-4 technical report, 2024
OpenAI, Josh Achiam, Steven Adler, Sandhini Agarwal, et al · 2024
Closest in time.
Performance analysis of Assistants versus Chat completion
OpenAI Dev. Forum · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
ReAct: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2023
Cited alongside, same era.
Language agent tree search unifies reasoning acting and planning in language models
Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, and Yu-Xiong Wang · 2023
Cited alongside, same era.
Large language models as planning domain generators
James Oswald, Kavitha Srinivas, Harsha Kokel, Junkyu Lee, Michael Katz, and Shirin Sohrabi · 2024
Closest in time.
Generalized planning in PDDL domains with pretrained large language models
Tom Silver, Soham Dan, Kavitha Srinivas, Josh Tenenbaum, Leslie Pack Kaelbling, and Michael Katz · 2024
Closest in time.