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Leveraging the Inductive Bias of Large Language Models for Abstract
  Textual Reasoning

Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning

5 October 2021
Christopher Rytting
David Wingate
    AI4CE
    LRM
ArXivPDFHTML

Papers citing "Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning"

6 / 6 papers shown
Title
"Tidy Up the Table": Grounding Common-sense Objective for Tabletop
  Object Rearrangement
"Tidy Up the Table": Grounding Common-sense Objective for Tabletop Object Rearrangement
Yiqing Xu
David Hsu
LM&Ro
LMTD
34
0
0
21 Jul 2023
ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning
ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning
O. Yu. Golovneva
Moya Chen
Spencer Poff
Martin Corredor
Luke Zettlemoyer
Maryam Fazel-Zarandi
Asli Celikyilmaz
ReLM
LRM
34
139
0
15 Dec 2022
Knowledge-augmented Deep Learning and Its Applications: A Survey
Knowledge-augmented Deep Learning and Its Applications: A Survey
Zijun Cui
Tian Gao
Kartik Talamadupula
Qiang Ji
39
18
0
30 Nov 2022
Polling Latent Opinions: A Method for Computational Sociolinguistics
  Using Transformer Language Models
Polling Latent Opinions: A Method for Computational Sociolinguistics Using Transformer Language Models
Philip G. Feldman
Aaron Dant
James R. Foulds
Shimei Pan
20
3
0
15 Apr 2022
Language Models as Knowledge Bases?
Language Models as Knowledge Bases?
Fabio Petroni
Tim Rocktaschel
Patrick Lewis
A. Bakhtin
Yuxiang Wu
Alexander H. Miller
Sebastian Riedel
KELM
AI4MH
454
2,589
0
03 Sep 2019
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
305
31,280
0
16 Jan 2013
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