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"What is on your mind?" Automated Scoring of Mindreading in Childhood
  and Early Adolescence

"What is on your mind?" Automated Scoring of Mindreading in Childhood and Early Adolescence

16 November 2020
Venelin Kovatchev
Phillip Smith
Mark G. Lee
Imogen Elizabeth Grumley Traynor
Irene Luque Aguilera
R. Devine
    ReLMLRM
ArXiv (abs)PDFHTML

Papers citing ""What is on your mind?" Automated Scoring of Mindreading in Childhood and Early Adolescence"

3 / 3 papers shown
Title
The State of Human-centered NLP Technology for Fact-checking
The State of Human-centered NLP Technology for Fact-checking
Anubrata Das
Houjiang Liu
Venelin Kovatchev
Matthew Lease
HILM
156
66
0
08 Jan 2023
longhorns at DADC 2022: How many linguists does it take to fool a
  Question Answering model? A systematic approach to adversarial attacks
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks
Venelin Kovatchev
Trina Chatterjee
Venkata S Govindarajan
Jifan Chen
Eunsol Choi
...
K. Erk
Matthew Lease
Junyi Jessy Li
Yating Wu
Kyle Mahowald
AAMLELM
105
9
0
29 Jun 2022
Can vectors read minds better than experts? Comparing data augmentation
  strategies for the automated scoring of children's mindreading ability
Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children's mindreading ability
Venelin Kovatchev
Phillip Smith
Mark G. Lee
R. Devine
77
6
0
03 Jun 2021
1