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Grounding Natural Language Instructions: Can Large Language Models
  Capture Spatial Information?

Grounding Natural Language Instructions: Can Large Language Models Capture Spatial Information?

17 September 2021
Julia Rozanova
Deborah Ferreira
K. Dubba
Weiwei Cheng
Dell Zhang
André Freitas
    LM&Ro
ArXiv (abs)PDFHTML

Papers citing "Grounding Natural Language Instructions: Can Large Language Models Capture Spatial Information?"

7 / 7 papers shown
Title
Does My Representation Capture X? Probe-Ably
Does My Representation Capture X? Probe-Ably
Deborah Ferreira
Julia Rozanova
Mokanarangan Thayaparan
Marco Valentino
André Freitas
33
11
0
12 Apr 2021
Probing Pretrained Language Models for Lexical Semantics
Probing Pretrained Language Models for Lexical Semantics
Ivan Vulić
Edoardo Ponti
Robert Litschko
Goran Glavaš
Anna Korhonen
KELM
74
246
0
12 Oct 2020
Pareto Probing: Trading Off Accuracy for Complexity
Pareto Probing: Trading Off Accuracy for Complexity
Tiago Pimentel
Naomi Saphra
Adina Williams
Ryan Cotterell
55
60
0
05 Oct 2020
Information-Theoretic Probing with Minimum Description Length
Information-Theoretic Probing with Minimum Description Length
Elena Voita
Ivan Titov
85
276
0
27 Mar 2020
LayoutLM: Pre-training of Text and Layout for Document Image
  Understanding
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
Yiheng Xu
Minghao Li
Lei Cui
Shaohan Huang
Furu Wei
Ming Zhou
135
707
0
31 Dec 2019
Designing and Interpreting Probes with Control Tasks
Designing and Interpreting Probes with Control Tasks
John Hewitt
Percy Liang
76
537
0
08 Sep 2019
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy
  Lifting, the Rest Can Be Pruned
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
Elena Voita
David Talbot
F. Moiseev
Rico Sennrich
Ivan Titov
114
1,146
0
23 May 2019
1