Zichao (Jack) Wang 王子超

Zichao (Jack) Wang
王子超

Machine intelligence for human intelligence

publications

EDU = education-related
NLP = natural language processing
ML   = machine learning | deep learning

2023

  1. Retrieval-based Controllable Molecule Generation ML
    Zichao Wang*, Weili Nie*, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar
    (*=equal contribution)
    International Conference on Learning Representations (ICLR), to appear, 2023

2022

  1. Open-Ended Knowledge Tracing EDU NLP
    Naiming Liu*, Zichao Wang*, Richard G. Baraniuk, Andrew Lan (*=equal contribution)
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
  2. Towards Human-like Educational Question Generation with Large Language Models EDU NLP
    Zichao Wang*, Jakob Valdez*, Debshila Basu Mallick, Richard G. Baraniuk (*=equal contribution)
    Conference on Artificial Intelligence in Education (AIED), 2022
  3. Automated Scoring for Reading Comprehension via In-context BERT Tuning EDU NLP
    Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew Lan
    Conference on Artificial Intelligence in Education (AIED), 2022
  4. DeepHull: Fast Convex Hull Approximation in High Dimensions ML
    Randall Balestriero*, Zichao Wang*, Richard G. Baraniuk (*=equal contribution)
    International Conference on Acoustics, Speech, & Signal Processing (ICASSP), 2022

2021

  1. Mathematical Formula Representation via Tree Embeddings NLP
    Zichao Wang, Mengxue Zhang, Andrew S. Lan, and Richard G. Baraniuk
    IEEE nternational Conference on Big Data (IEEE BigData), 2021
  2. Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints NLP
    Zichao Wang, Andrew S. Lan, and Richard G. Baraniuk
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021
  3. Math Operation Embeddings for Open-ended Solution Analysis and Feedback EDU
    Mengxue Zhang, Zichao Wang, Richard G. Baraniuk, and Andrew S. Lan
    International Conference on Educational Data Mining (EDM), 2021
  4. Towards Bloom’s Taxonomy Classification Without Any Labels EDU
    Zichao Wang, Kyle Manning, Debshila Basu Mallick, and Richard G. Baraniuk
    Conference on Artificial Intelligence in Education (AIED), 2021
  5. The Recurrent Neural Tangent Kernel ML
    Sina Alemohammad, Zichao Wang, Randall Balestriero, and Richard G. Baraniuk
    International Conference on Learning Representations (ICLR), 2021
  6. Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels ML
    Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, and Richard G. Baraniuk
    International Conference on Acoustics, Speech, & Signal Processing (ICASSP), 2021
  7. Large-Scale Educational Question Analysis with Partial Variational Auto-encoders EDU ML
    Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon P. Jones, Richard G. Baraniuk, and Cheng Zhang
    Symposium on Educational Advances in Artificial Intelligence (AAAI-EAAI), 2021

2020

  1. Scalable Neural Tangent Kernel of Recurrent Architectures ML
    Sina Alemohammad, Randall Balestriero, Zichao Wang, and Richard G. Baraniuk
    arXiv preprint, 2020
  2. Diagnostic Questions: The NeurIPS 2020 Education Challenge EDU
    Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon P. Jones, and Cheng Zhang
    arXiv preprint, 2020
  3. VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics EDU ML
    Zichao Wang, Yi Gu, Andrew S. Lan, and Richard G. Baraniuk
    International Conference on Educational Data Mining (EDM), 2020

2019

  1. A Max Affine Spline Perspective of Recurrent Neural Networks ML
    Zichao Wang, Randall Balestriero, and Richard G. Baraniuk
    International Conference on Learning Representations (ICLR), 2019
  2. A Meta-Learning Augmented Bidirectional Transformer Model for Automatic Short Answer Grading EDU NLP
    Zichao Wang, Andrew S. Lan, Andrew E. Waters, Phillip J. Grimaldi, and Richard G. Baraniuk
    International Conference on Educational Data Mining (EDM), 2019

2018

  1. QG-Net: A Data-driven Question Generation Model for Educational Content EDU NLP
    Zichao Wang, Andrew S. Lan, Weili Nie, Andrew E. Waters, Phillip J. Grimaldi, and Richard G. Baraniuk
    ACM Conference on Learning at Scale (L@S), 2018

2017

  1. A Latent Factor Model for Instructor Content Preference Analysis EDU ML
    Zichao Wang, Andrew S. Lan, Phillip J. Grimaldi, and Richard G. Baraniuk
    International Conference on Educational Data Mining (EDM), 2017

2016

  1. Constrained Multi-channel Linear Prediction for Adaptive Speech Dereverberation ML
    Ante Jukić, Zichao Wang, Toon Waterschoot, Timo Gerkmann, and Simon Doclo
    IEEE International Workshop on Acoustic Signal Enhancement (IWAENC), 2016