Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models

3 August 2023

Papers citing "Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models"

8 / 8 papers shown

Title
Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora Alex Warstadt Aaron Mueller Leshem Choshen E. Wilcox Chengxu Zhuang ... Rafael Mosquera Bhargavi Paranjape Adina Williams Tal Linzen Ryan Cotterell 38 106 0 10 Apr 2025
BERTtime Stories: Investigating the Role of Synthetic Story Data in Language Pre-training Nikitas Theodoropoulos Giorgos Filandrianos Vassilis Lyberatos Maria Lymperaiou Giorgos Stamou SyDa 52 1 0 24 Feb 2025
Pre-Training to Learn in Context Yuxian Gu Li Dong Furu Wei Minlie Huang CLIP LRM ReLM 108 37 0 16 May 2023
Generate rather than Retrieve: Large Language Models are Strong Context Generators W. Yu Dan Iter Shuohang Wang Yichong Xu Mingxuan Ju Soumya Sanyal Chenguang Zhu Michael Zeng Meng-Long Jiang RALM AIMat 221 321 0 21 Sep 2022
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 295 4,077 0 24 May 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 315 8,448 0 28 Jan 2022
Word Acquisition in Neural Language Models Tyler A. Chang Benjamin Bergen 27 39 0 05 Oct 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,950 0 20 Apr 2018