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Instructing the model to generate a sequence of intermediate steps, a.k.a., a chain of thought (CoT), is a highly effective method to improve the accuracy of large language models (LLMs) on arithmetics and symbolic reasoning tasks.
Algebraic theory of machines. i. prime decomposition theorem for finite semigroups and machines
Kenneth Krohn and John Rhodes · 1965
Earlier work this paper cites.
Counter-Free Automata (MIT research monograph no. 65)
Robert McNaughton and Seymour A Papert · 1971
Earlier work this paper cites.
Relations among complexity measures
Nicholas Pippenger and Michael J Fischer · 1979
Earlier work this paper cites.
Unbounded fan-in circuits and associative functions
Ashok K Chandra, Steven Fortune, and Richard Lipton · 1983
Earlier work this paper cites.
Relativized circuit complexity
Christopher B Wilson · 1985
Earlier work this paper cites.
Bounded-width polynomial-size branching programs recognize exactly those languages in nc
David A. Barrington · 1986
Earlier work this paper cites.
Circuits and local computation
Andrew Chi-Chih Yao · 1989
Earlier work this paper cites.
What every computer scientist should know about floating-point arithmetic
David Goldberg · 1991
Earlier work this paper cites.
Time-lock puzzles and timed-release crypto
Ronald L Rivest, Adi Shamir, and David A Wagner · 1996
Earlier work this paper cites.
Division is in uniform tc0
William Hesse · 2001
Earlier work this paper cites.
Ieee standard for floating-point arithmetic
IEEE · 2008
Earlier work this paper cites.
On the krohn-rhodes cascaded decomposition theorem
Oded Maler · 2010
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
Earlier work this paper cites.
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Wang Ling, Dani Yogatama, Chris Dyer, and Phil Blunsom · 2017
Earlier work this paper cites.
Mostafa Dehghani, Stephan Gouws, Oriol Vinyals, Jakob Uszkoreit, and 𝖫 \mathsf{L} ukasz Kaiser · 2018
Earlier work this paper cites.
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