Simon Woodhead

According to our database, Simon Woodhead authored at least 19 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions.

Nigel Fernandez, Alexander Scarlatos, Simon Woodhead, Andrew S. Lan

CoRR, 2024

Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models.

Wanyong Feng, Jaewook Lee, Hunter McNichols, Alexander Scarlatos, Digory Smith, Simon Woodhead, Nancy Otero Ornelas, Andrew S. Lan

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions.

Nigel Fernandez, Alexander Scarlatos, Wanyong Feng, Simon Woodhead, Andrew S. Lan

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Math Multiple Choice Question Generation via Human-Large Language Model Collaboration.

Jaewook Lee, Digory Smith, Simon Woodhead, Andrew S. Lan

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Improving Automated Distractor Generation for Math Multiple-choice Questions with Overgenerate-and-rank.

Alexander Scarlatos, Wanyong Feng, Andrew S. Lan, Simon Woodhead, Digory Smith

Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications, 2024

Improving the Validity of Automatically Generated Feedback via Reinforcement Learning.

Alexander Scarlatos, Digory Smith, Simon Woodhead, Andrew S. Lan

Proceedings of the Artificial Intelligence in Education - 25th International Conference, 2024

2023

Novice Learner and Expert Tutor: Evaluating Math Reasoning Abilities of Large Language Models with Misconceptions.

Naiming Liu, Shashank Sonkar, Zichao Wang, Simon Woodhead, Richard G. Baraniuk

CoRR, 2023

Exploring Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context Learning.

Hunter McNichols, Wanyong Feng, Jaewook Lee, Alexander Scarlatos, Digory Smith, Simon Woodhead, Andrew S. Lan

CoRR, 2023

Towards the Future of AI-Augmented Human Tutoring in Math Learning.

Vincent Aleven, Richard G. Baraniuk, Emma Brunskill, Scott Crossley, Dora Demszky, Stephen Fancsali, Shivang Gupta, Kenneth R. Koedinger, Chris Piech, Steven Ritter, Danielle R. Thomas, Simon Woodhead, Wanli Xing

Proceedings of the Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky, 2023

2022

Instructions and Guide: Causal Insights for Learning Paths in Education.

Wenbo Gong, Digory Smith, Zichao Wang, Craig Barton, Simon Woodhead, Nick Pawlowski, Joel Jennings, Cheng Zhang

CoRR, 2022

Simultaneous Missing Value Imputation and Structure Learning with Groups.

Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CoRGi: Content-Rich Graph Neural Networks with Attention.

Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zhang, Miltiadis Allamanis

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

VICause: Simultaneous Missing Value Imputation and Causal Discovery with Groups.

Pablo Morales-Alvarez, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Miltiadis Allamanis, Cheng Zhang

CoRR, 2021

CoRGi: Content-Rich Graph Neural Networks with Attention.

Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zheng, Miltiadis Allamanis

CoRR, 2021

Contextual HyperNetworks for Novel Feature Adaptation.

Angus Lamb, Evgeny Saveliev, Yingzhen Li, Sebastian Tschiatschek, Camilla Longden, Simon Woodhead, José Miguel Hernández-Lobato, Richard E. Turner, Pashmina Cameron, Cheng Zhang

CoRR, 2021

Educational Question Mining At Scale: Prediction, Analysis and Personalization.

Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Diagnostic Questions: The NeurIPS 2020 Education Challenge.

Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang

CoRR, 2020

Large-Scale Educational Question Analysis with Partial Variational Auto-encoders.

Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Cheng Zhang

CoRR, 2020

Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge.

Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020