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2002.00276
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Variational Item Response Theory: Fast, Accurate, and Expressive
Educational Data Mining (EDM), 2020
1 February 2020
Mike Wu
R. Davis
B. Domingue
Chris Piech
Noah D. Goodman
OffRL
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Papers citing
"Variational Item Response Theory: Fast, Accurate, and Expressive"
24 / 24 papers shown
Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response Theory
Hongli Zhou
Hui Huang
Ziqing Zhao
Lvyuan Han
Huicheng Wang
...
Jian Dong
Bing Xu
Conghui Zhu
Hailong Cao
Tiejun Zhao
ALM
493
13
0
21 May 2025
Reliable and Efficient Amortized Model-based Evaluation
Sang T. Truong
Yuheng Tu
Abigail Z. Jacobs
Yue Liu
Sanmi Koyejo
ELM
425
13
0
17 Mar 2025
Generative Adversarial Networks for High-Dimensional Item Factor Analysis: A Deep Adversarial Learning Algorithm
Nanyu Luo
Feng Ji
DRL
533
1
0
15 Feb 2025
Introducing Flexible Monotone Multiple Choice Item Response Theory Models and Bit Scales
Joakim Wallmark
Maria Josefsson
Marie Wiberg
141
2
0
02 Oct 2024
A Psychology-based Unified Dynamic Framework for Curriculum Learning
Computational Linguistics (CL), 2024
Guangyu Meng
Qingkai Zeng
John P. Lalor
Hong-ye Yu
303
1
0
09 Aug 2024
Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models
Joy He-Yueya
Wanjing Anya Ma
Kanishk Gandhi
Benjamin W. Domingue
Emma Brunskill
Noah D. Goodman
ALM
230
13
0
22 Jul 2024
A Survey of Models for Cognitive Diagnosis: New Developments and Future Directions
Fei Wang
Weibo Gao
Qi Liu
Jiatong Li
Guanhao Zhao
...
Zhenya Huang
Mengxiao Zhu
Shijin Wang
Wei Tong
Tong Xu
AI4Ed
343
15
0
07 Jul 2024
Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing
Han Jiang
Xiaoyuan Yi
Zhihua Wei
Ziang Xiao
Shu Wang
Xing Xie
ELM
ALM
735
20
0
20 Jun 2024
Survey of Computerized Adaptive Testing: A Machine Learning Perspective
Yan Zhuang
Zhuang Yan
Haoyang Bi
Zhenya Huang
Weizhe Huang
...
Z. Pardos
Haiping Ma
Mengxiao Zhu
Shijin Wang
Enhong Chen
AI4Ed
ELM
301
24
0
31 Mar 2024
Generative AI for Education (GAIED): Advances, Opportunities, and Challenges
Paul Denny
Sumit Gulwani
Neil T. Heffernan
Tanja Käser
Steven Moore
Anna N. Rafferty
Adish Singla
341
34
0
02 Feb 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families
International Conference on Machine Learning (ICML), 2024
Joohwan Ko
Kyurae Kim
W. Kim
Jacob R. Gardner
BDL
606
6
0
19 Jan 2024
Training Reinforcement Learning Agents and Humans With Difficulty-Conditioned Generators
Sidney Tio
Jimmy Ho
Pradeep Varakantham
OffRL
170
1
0
04 Dec 2023
Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm
The Web Conference (WWW), 2023
Jiatong Li
Qi Liu
Fei-Yue Wang
Jia-Yin Liu
Zhenya Huang
Fangzhou Yao
Linbo Zhu
Yu Su
AI4Ed
303
19
0
01 Sep 2023
Amortised Design Optimization for Item Response Theory
International Conference on Artificial Intelligence in Education (AIED), 2023
Antti Keurulainen
Isak Westerlund
Oskar Keurulainen
Andrew Howes
182
0
0
19 Jul 2023
Knowledge Graph Enhanced Intelligent Tutoring System Based on Exercise Representativeness and Informativeness
International Journal of Intelligent Systems (IJIS), 2023
Linqing Li
Zhifeng Wang
AI4Ed
185
23
0
15 Jul 2023
Transferable Curricula through Difficulty Conditioned Generators
International Joint Conference on Artificial Intelligence (IJCAI), 2023
Sidney Tio
Pradeep Varakantham
266
5
0
22 Jun 2023
Computational modeling of semantic change
Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2023
Nina Tahmasebi
Haim Dubossarsky
367
8
0
13 Apr 2023
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems
Jill-Jênn Vie
Tomas Rigaux
H. Kashima
BDL
308
1
0
20 Dec 2022
Foundation Posteriors for Approximate Probabilistic Inference
Neural Information Processing Systems (NeurIPS), 2022
Mike Wu
Noah D. Goodman
UQCV
268
7
0
19 May 2022
py-irt: A Scalable Item Response Theory Library for Python
INFORMS journal on computing (IJOC), 2022
John P. Lalor
Pedro Rodriguez
392
20
0
02 Mar 2022
Deep Learning-Based Estimation and Goodness-of-Fit for Large-Scale Confirmatory Item Factor Analysis
Christopher J. Urban
Daniel J. Bauer
CML
230
2
0
20 Sep 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts
International Conference on Machine Learning (ICML), 2020
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Abigail Z. Jacobs
OOD
776
1,744
0
14 Dec 2020
VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics
Educational Data Mining (EDM), 2020
Zichao Wang
Yi Gu
Andrew Lan
Richard Baraniuk
306
12
0
27 May 2020
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis
Christopher J. Urban
Daniel J. Bauer
BDL
541
38
0
22 Jan 2020
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