Fetching the paper…
Reading the bibliography…
Language models are increasingly being deployed for general problem solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making processes during inference.
Report on a general problem solving program
A. Newell, J. C. Shaw, and H. A. Simon · 1959
Earlier work this paper cites.
A formal basis for the heuristic determination of minimum cost paths
P. E. Hart, N. J. Nilsson, and B. Raphael · 1968
Earlier work this paper cites.
Human problem solving
A. Newell, H. A. Simon, et al · 1972
Earlier work this paper cites.
The empirical case for two systems of reasoning
S. A. Sloman · 1996
Earlier work this paper cites.
Who is rational? Studies of individual differences in reasoning
K. E. Stanovich · 1999
Earlier work this paper cites.
Deep blue
M. Campbell, A. J. Hoane Jr, and F.-h. Hsu · 2002
Earlier work this paper cites.
Representativeness revisited: Attribute substitution in intuitive judgment
D. Kahneman, S. Frederick, et al · 2002
Earlier work this paper cites.
Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control
N. D. Daw, Y. Niv, and P. Dayan · 2005
Earlier work this paper cites.
Thinking, fast and slow
D. Kahneman · 2011
Earlier work this paper cites.
A survey of monte carlo tree search methods
C. Browne, E. J. Powley, D. Whitehouse, S. M. M. Lucas, P. I. Cowling, P. Rohlfshagen, S. Tavener, D. P. Liebana, S. Samothrakis, and S. Colton · 2012
Earlier work this paper cites.
Mastering the game of go without human knowledge
D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, et al · 2017
Earlier work this paper cites.
Improving language understanding by generative pre-training
A. Radford, K. Narasimhan, T. Salimans, I. Sutskever, et al · 2018
Earlier work this paper cites.
Language models are unsupervised multitask learners
A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, I. Sutskever, et al · 2019
Earlier work this paper cites.
Language models are few-shot learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al · 2020
Cited alongside, same era.
Neurologic a*esque decoding: Constrained text generation with lookahead heuristics
X. Lu, S. Welleck, P. West, L. Jiang, J. Kasai, D. Khashabi, R. L. Bras, L. Qin, Y. Yu, R. Zellers, N. A. Smith, and Y. Choi · 2021
Cited alongside, same era.
Palm: Scaling language modeling with pathways
A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann, et al · 2022
Cited alongside, same era.
Faithful reasoning using large language models
A. Creswell and M. Shanahan · 2022
Cited alongside, same era.
Maieutic prompting: Logically consistent reasoning with recursive explanations
J. Jung, L. Qin, S. Welleck, F. Brahman, C. Bhagavatula, R. L. Bras, and Y. Choi · 2022
Pal: Program-aided language models, 2023
L. Gao, A. Madaan, S. Zhou, U. Alon, P. Liu, Y. Yang, J. Callan, and G. Neubig · 2023
Closest in time.
Reasoning with language model is planning with world model
S. Hao, Y. Gu, H. Ma, J. J. Hong, Z. Wang, D. Z. Wang, and Z. Hu · 2023
Closest in time.
Language models can solve computer tasks, 2023
G. Kim, P. Baldi, and S. McAleer · 2023
Closest in time.
Llm+p: Empowering large language models with optimal planning proficiency, 2023
B. Liu, Y. Jiang, X. Zhang, Q. Liu, S. Zhang, J. Biswas, and P. Stone · 2023
Closest in time.
Self-refine: Iterative refinement with self-feedback, 2023
A. Madaan, N. Tandon, P. Gupta, S. Hallinan, L. Gao, S. Wiegreffe, U. Alon, N. Dziri, S. Prabhumoye, Y. Yang, S. Welleck, B. P. Majumder, S. Gupta, A. Yazdanbakhsh, and P. Clark · 2023
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.
Chai: A chatbot ai for task-oriented dialogue with offline reinforcement learning
S. Verma, J. Fu, S. Yang, and S. Levine · 2022
Cited alongside, same era.
E. Wallace, N. Tomlin, A. Xu, K. Yang, E. Pathak, M. Ginsberg, and D. Klein · 2022
Cited alongside, same era.
Self-consistency improves chain of thought reasoning in language models
X. Wang, J. Wei, D. Schuurmans, Q. Le, E. Chi, and D. Zhou · 2022
Cited alongside, same era.
Chain of thought prompting elicits reasoning in large language models
J. Wei, X. Wang, D. Schuurmans, M. Bosma, E. Chi, Q. Le, and D. Zhou · 2022
Cited alongside, same era.
ReAct: Synergizing reasoning and acting in language models
S. Yao, J. Zhao, D. Yu, N. Du, I. Shafran, K. Narasimhan, and Y. Cao · 2022
Cited alongside, same era.
Least-to-most prompting enables complex reasoning in large language models
D. Zhou, N. Schärli, L. Hou, J. Wei, N. Scales, X. Wang, D. Schuurmans, C. Cui, O. Bousquet, Q. Le, et al · 2022
Cited alongside, same era.
Solving math word problem via cooperative reasoning induced language models
X. Zhu, J. Wang, L. Zhang, Y. Zhang, R. Gan, J. Zhang, and Y. Yang · 2022
Cited alongside, same era.
OpenAI · 2023
Closest in time.
Refiner: Reasoning feedback on intermediate representations, 2023
D. Paul, M. Ismayilzada, M. Peyrard, B. Borges, A. Bosselut, R. West, and B. Faltings · 2023
Closest in time.
Large language model programs, 2023
I. Schlag, S. Sukhbaatar, A. Celikyilmaz, W. tau Yih, J. Weston, J. Schmidhuber, and X. Li · 2023
Closest in time.
Reflexion: an autonomous agent with dynamic memory and self-reflection, 2023
N. Shinn, B. Labash, and A. Gopinath · 2023
Closest in time.
Llama: Open and efficient foundation language models
H. Touvron, T. Lavril, G. Izacard, X. Martinet, M.-A. Lachaux, T. Lacroix, B. Rozière, N. Goyal, E. Hambro, F. Azhar, et al · 2023
Closest in time.
Decomposition enhances reasoning via self-evaluation guided decoding, 2023
Y. Xie, K. Kawaguchi, Y. Zhao, X. Zhao, M.-Y. Kan, J. He, and Q. Xie · 2023
Closest in time.
Foundation models for decision making: Problems, methods, and opportunities, 2023
S. Yang, O. Nachum, Y. Du, J. Wei, P. Abbeel, and D. Schuurmans · 2023
Closest in time.
Planning with large language models for code generation
S. Zhang, Z. Chen, Y. Shen, M. Ding, J. B. Tenenbaum, and C. Gan · 2023
Closest in time.