Large Language Model for Science: A Study on P vs. NP
In this work, we use large language models (LLMs) to augment and accelerate
research on the P versus NP problem, one of the most important open problems in
theoretical computer science and mathematics. Specifically, we propose Socratic
reasoning, a general framework that promotes in-depth thinking with LLMs for
complex problem-solving. Socratic reasoning encourages LLMs to recursively
discover, solve, and integrate problems while facilitating self-evaluation and
refinement. Our pilot study on the P vs. NP problem shows that GPT-4
successfully produces a proof schema and engages in rigorous reasoning
throughout 97 dialogue turns, concluding "P neq NP", which is in alignment
with (Xu and Zhou, 2023). The investigation uncovers novel insights within the
extensive solution space of LLMs, shedding light on LLM for Science.
65010a115d76377562ceeac0
Qingxiu Dong
claimed_verified
2024-10-10T08:03:15.668Z
670740744341dcee459fb990
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/66UkZvrAk7fQr5YCylEFk.png
Qingxiu Dong
user
Rsy24
65010a115d76377562ceeac1
Li Dong
claimed_verified
2024-10-08T15:19:42.871Z
5df85abada6d0311fd3d5408
/avatars/2331cf703c1b5d3a62e2050b1a6eb108.svg
Li Dong
user
unilm
65010a115d76377562ceeac2
Ke Xu
65010a115d76377562ceeac3
Guangyan Zhou
admin_assigned
2023-09-13T13:22:25.070Z
64be1cc181caff7f183a3c2b
/avatars/5206fc6fc3491c79f7012f5cc67c8a45.svg
Guangyan Zhou
user
Chiken1
65010a115d76377562ceeac4
Yaru Hao
65010a115d76377562ceeac5
Zhifang Sui
65010a115d76377562ceeac6
Furu Wei
admin_assigned
2023-09-13T13:23:18.350Z
6368c512fbfe97c16a40baba
/avatars/1c23bc7c0b6d9225699ce27647623d7a.svg
Furu Wei
user
thegenerality
Large Language Model for Science: A Study on P vs. NP
In this work, we use large language models (LLMs) to augment and accelerate
research on the P versus NP problem, one of the most important open problems in
theoretical computer science and mathematics. Specifically, we propose Socratic
reasoning, a general framework that promotes in-depth thinking with LLMs for
complex problem-solving. Socratic reasoning encourages LLMs to recursively
discover, solve, and integrate problems while facilitating self-evaluation and
refinement. Our pilot study on the P vs. NP problem shows that GPT-4
successfully produces a proof schema and engages in rigorous reasoning
throughout 97 dialogue turns, concluding "P neq NP", which is in alignment
with (Xu and Zhou, 2023). The investigation uncovers novel insights within the
extensive solution space of LLMs, shedding light on LLM for Science.
LLMs, using Socratic reasoning, generate a proof schema and engage in rigorous dialogue to address the P vs. NP problem, aligning with existing research.
large language models LLMs Socratic reasoning recursive discovery proof schema dialogue turns