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Automatically Detecting Confusion and Conflict During Collaborative
  Learning Using Linguistic, Prosodic, and Facial Cues

Automatically Detecting Confusion and Conflict During Collaborative Learning Using Linguistic, Prosodic, and Facial Cues

26 January 2024
Yingbo Ma
Yukyeong Song
Mehmet Celepkolu
K. Boyer
Eric Wiebe
Collin F. Lynch
Maya Israel
ArXivPDFHTML

Papers citing "Automatically Detecting Confusion and Conflict During Collaborative Learning Using Linguistic, Prosodic, and Facial Cues"

3 / 3 papers shown
Title
Informer: Beyond Efficient Transformer for Long Sequence Time-Series
  Forecasting
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Haoyi Zhou
Shanghang Zhang
J. Peng
Shuai Zhang
Jianxin Li
Hui Xiong
Wan Zhang
AI4TS
161
3,799
0
14 Dec 2020
EmoNets: Multimodal deep learning approaches for emotion recognition in
  video
EmoNets: Multimodal deep learning approaches for emotion recognition in video
Samira Ebrahimi Kahou
Xavier Bouthillier
Pascal Lamblin
Çağlar Gülçehre
Vincent Michalski
...
Aaron Courville
Pascal Vincent
Roland Memisevic
C. Pal
Yoshua Bengio
119
400
0
05 Mar 2015
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh V. Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
154
25,150
0
09 Jun 2011
1