FAC $^2$ E: Better Understanding Large Language Model Capabilities by Dissociating Language and Cognition

29 February 2024

Papers citing "FAC$^2$E: Better Understanding Large Language Model Capabilities by Dissociating Language and Cognition"

6 / 6 papers shown

Title
LESS: Selecting Influential Data for Targeted Instruction Tuning Mengzhou Xia Sadhika Malladi Suchin Gururangan Sanjeev Arora Danqi Chen 80 185 0 06 Feb 2024
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 308 11,909 0 04 Mar 2022
Think Before You Speak: Explicitly Generating Implicit Commonsense Knowledge for Response Generation Pei Zhou Karthik Gopalakrishnan Behnam Hedayatnia Seokhwan Kim Jay Pujara Xiang Ren Yang Liu Dilek Z. Hakkani-Tür 34 40 0 16 Oct 2021
On Extractive and Abstractive Neural Document Summarization with Transformer Language Models Sandeep Subramanian Raymond Li Jonathan Pilault C. Pal 233 214 0 07 Sep 2019
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 408 2,584 0 03 Sep 2019
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 297 6,950 0 20 Apr 2018