When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1

Reading the bibliography…

Fetching the paper…

Built on

Toward a universal law of generalization for psychological science
Roger N. Shepard. 1987 · 1987
Earlier work this paper cites.
The Adaptive Character of Thought
John R Anderson. 1990 · 1990
Earlier work this paper cites.
Finding structure in time
Jeffrey L Elman. 1990 · 1990
Earlier work this paper cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
Earlier work this paper cites.

Understanding human intelligence through human limitations
Thomas L Griffiths. 2020 · 2020
Cited alongside, same era.
Show your work: Scratchpads for intermediate computation with language models
Original
Maxwell Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, Charles Sutton, and Augustus Odena. 2021 · 2021
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
Cited alongside, same era.

Sparks of artificial general intelligence: Early experiments with GPT-4
Original
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, and Yi Zhang. 2023 · 2023
Later among the works it cites.
Embers of autoregression: Understanding large language models through the problem they are trained to solve
Original
R. Thomas McCoy, Shunyu Yao, Dan Friedman, Mathew Hardy, and Thomas L. Griffiths. 2023 · 2023
Later among the works it cites.
Deciphering the factors influencing the efficacy of chain-of-thought: Probability, memorization, and noisy reasoning
Original
Akshara Prabhakar, Thomas L. Griffiths, and R. Thomas McCoy. 2024 · 2024
Closest in time.

alphaXiv searches the wider corpus for related work and actual follow-ups.

alphaXiv is searching for related work…

Reading the bibliography…

When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1 · Around

Toward a universal law of generalization for psychological science
Roger N. Shepard. 1987 · 1987
Earlier work this paper cites.
The Adaptive Character of Thought
John R Anderson. 1990 · 1990
Earlier work this paper cites.
Finding structure in time
Jeffrey L Elman. 1990 · 1990
Earlier work this paper cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
Earlier work this paper cites.

Understanding human intelligence through human limitations
Thomas L Griffiths. 2020 · 2020
Cited alongside, same era.
Show your work: Scratchpads for intermediate computation with language models
Original
Maxwell Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, Charles Sutton, and Augustus Odena. 2021 · 2021
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
Cited alongside, same era.

Sparks of artificial general intelligence: Early experiments with GPT-4
Original
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, and Yi Zhang. 2023 · 2023
Later among the works it cites.
Embers of autoregression: Understanding large language models through the problem they are trained to solve
Original
R. Thomas McCoy, Shunyu Yao, Dan Friedman, Mathew Hardy, and Thomas L. Griffiths. 2023 · 2023
Later among the works it cites.
Deciphering the factors influencing the efficacy of chain-of-thought: Probability, memorization, and noisy reasoning
Original
Akshara Prabhakar, Thomas L. Griffiths, and R. Thomas McCoy. 2024 · 2024
Closest in time.

alphaXiv searches the wider corpus for related work and actual follow-ups.

alphaXiv is searching for related work…