Long Is More Important Than Difficult for Training Reasoning Models

23 March 2025

Papers citing "Long Is More Important Than Difficult for Training Reasoning Models"

8 / 8 papers shown

Title
S*: Test Time Scaling for Code Generation Dacheng Li Shiyi Cao Chengkun Cao Xiuyu Li Shangyin Tan Kurt Keutzer Jiarong Xing Joseph E. Gonzalez Ion Stoica LRM VLM 72 12 0 21 Feb 2025
SIFT: Grounding LLM Reasoning in Contexts via Stickers Zihao Zeng Xuyao Huang Boxiu Li Zhijie Deng LRM 46 2 0 19 Feb 2025
LIMO: Less is More for Reasoning Yixin Ye Zhen Huang Yang Xiao Ethan Chern Shijie Xia Pengfei Liu LRM 146 140 0 05 Feb 2025
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters Charlie Snell Jaehoon Lee Kelvin Xu Aviral Kumar LRM 143 626 0 06 Aug 2024
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct Haipeng Luo Qingfeng Sun Can Xu Pu Zhao Jian-Guang Lou ... Xiubo Geng Qingwei Lin Shifeng Chen Yansong Tang Dongmei Zhang LRM OSLM 187 447 0 18 Aug 2023
Training Compute-Optimal Large Language Models Jordan Hoffmann Sebastian Borgeaud A. Mensch Elena Buchatskaya Trevor Cai ... Karen Simonyan Erich Elsen Jack W. Rae Oriol Vinyals Laurent Sifre AI4TS 180 1,941 0 29 Mar 2022
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 672 41,736 0 28 May 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 532 4,773 0 23 Jan 2020