Fetching the paper…
Reading the bibliography…
Generative neural models hold great promise in enhancing programming education by synthesizing new content.
Symbolic Execution and Program Testing
James C. King · 1976
Earlier work this paper cites.
Karel the Robot: A Gentle Introduction to the Art of Programming
Richard E Pattis, Jim Roberts, and Mark Stehlik · 1995
Earlier work this paper cites.
Long Short-Term Memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Bandit based Monte-Carlo Planning
Levente Kocsis and Csaba Szepesvári · 2006
Earlier work this paper cites.
Scratch: Programming for All
Mitchel Resnick, John H. Maloney, Andrés Monroy-Hernández, Natalie Rusk, Evelyn Eastmond, Karen Brennan, Amon Millner, Eric Rosenbaum, Jay S. Silver, Brian Silverman, and Yasmin B. Kafai · 2009
Earlier work this paper cites.
Automatically Generating Algebra Problems
Rohit Singh, Sumit Gulwani, and Sriram K. Rajamani · 2012
Earlier work this paper cites.
Automatically Generating Problems and Solutions for Natural deduction
Umair Z. Ahmed, Sumit Gulwani, and Amey Karkare · 2013
Earlier work this paper cites.
Synthesis of Geometry Proof Problems
Chris Alvin, Sumit Gulwani, Rupak Majumdar, and Supratik Mukhopadhyay · 2014
Earlier work this paper cites.
Example-based Learning in Computer-aided STEM Education
Sumit Gulwani · 2014
Earlier work this paper cites.
Autonomously Generating Hints by Inferring Problem Solving Policies
Chris Piech, Mehran Sahami, Jonathan Huang, and Leonidas J. Guibas · 2015
Earlier work this paper cites.
Personalized Mathematical Word Problem Generation
Oleksandr Polozov, Eleanor O’Rourke, Adam M. Smith, Luke Zettlemoyer, Sumit Gulwani, and Zoran Popovic · 2015
Earlier work this paper cites.
Data Driven Sokoban Puzzle Generation with Monte Carlo Tree Search
Bilal Kartal, Nick Sohre, and Stephen J. Guy · 2016
Earlier work this paper cites.
DeepCoder: Learning to Write Programs
Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin, and Daniel Tarlow · 2017
Earlier work this paper cites.
RobustFill: Neural Program Learning under Noisy I/O
Jacob Devlin, Jonathan Uesato, Surya Bhupatiraju, Rishabh Singh, Abdel-rahman Mohamed, and Pushmeet Kohli · 2017
Earlier work this paper cites.
Program Synthesis
Sumit Gulwani, Oleksandr Polozov, Rishabh Singh, et al · 2017
Earlier work this paper cites.
Position Paper: Block-Based Programming Should Offer Intelligent Support for Learners
Thomas W. Price and Tiffany Barnes · 2017
Earlier work this paper cites.
A Syntactic Neural Model for General-Purpose Code Generation
Pengcheng Yin and Graham Neubig · 2017
Earlier work this paper cites.
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis
Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, and Pushmeet Kohli · 2018
Earlier work this paper cites.
Musegan: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment
Hao-Wen Dong, Wen-Yi Hsiao, Li-Chia Yang, and Yi-Hsuan Yang · 2018
Earlier work this paper cites.
Reinforcement Learning: An Introduction
Richard S. Sutton and Andrew G. Barto · 2018
Cited alongside, same era.
Synthetic Datasets for Neural Program Synthesis
Richard Shin, Neel Kant, Kavi Gupta, Chris Bender, Brandon Trabucco, Rishabh Singh, and Dawn Song · 2019
Cited alongside, same era.
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference
Mike Wu, Milan Mosse, Noah D. Goodman, and Chris Piech · 2019
Cited alongside, same era.
Exploring the Impact of Worked Examples in a Novice Programming Environment
Rui Zhi, Thomas W. Price, Samiha Marwan, Alexandra Milliken, Tiffany Barnes, and Min Chi · 2019
Cited alongside, same era.
Synthesizing Tasks for Block-based Programming
Umair Z. Ahmed, Maria Christakis, Aleksandr Efremov, Nigel Fernandez, Ahana Ghosh, Abhik Roychoudhury, and Adish Singla · 2020
Cited alongside, same era.
Deep Learning Techniques for Music Generation
Jean-Pierre Briot, Gaëtan Hadjeres, and François-David Pachet · 2020
Incoder: A Generative model for Code Infilling and Synthesis
Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, and Mike Lewis · 2022
Later among the works it cites.
Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes
Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, and Adish Singla · 2022
Later among the works it cites.
Towards Reasoning in Large Language Models: A Survey
Jie Huang and Kevin Chen-Chuan Chang · 2022
Later among the works it cites.
Coderl: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning
Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, and Steven Chu-Hong Hoi · 2022
Later among the works it cites.
Competition-Level Code Generation with Alphacode
Yujia Li et al · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Zero-shot Learning of Hint Policy via Reinforcement Learning and Program Synthesis
Aleksandr Efremov, Ahana Ghosh, and Adish Singla · 2020
Cited alongside, same era.
Codebert: A Pre-Trained Model for Programming and Natural Languages
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, and Ming Zhou · 2020
Cited alongside, same era.
The Synthesizability of Molecules Proposed by Generative Models
Wenhao Gao and Connor W Coley · 2020
Cited alongside, same era.
Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis
Kavi Gupta, Peter Ebert Christensen, Xinyun Chen, and Dawn Song · 2020
Cited alongside, same era.
Rethinking Drug Design in the Artificial Intelligence Era
Petra Schneider, W Patrick Walters, Alleyn T Plowright, Norman Sieroka, Jennifer Listgarten, Robert A Goodnow Jr, Jasmin Fisher, Johanna M Jansen, José S Duca, Thomas S Rush, et al · 2020
Cited alongside, same era.
Assessing the Impact of Generative AI on Medicinal Chemistry
W. Walters and Mark Murcko · 2020
Cited alongside, same era.
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Later among the works it cites.
Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models
Sami Sarsa, Paul Denny, Arto Hellas, and Juho Leinonen · 2022
Later among the works it cites.
Large Language Models Still Can’t Plan (A Benchmark for LLMs on Planning and Reasoning about Change)
Karthik Valmeekam, Alberto Olmo Hernandez, Sarath Sreedharan, and Subbarao Kambhampati · 2022
Later among the works it cites.
Have LLMs Advanced Enough? A Challenging Problem Solving Benchmark For Large Language Models
Daman Arora, Himanshu Gaurav Singh, and Mausam · 2023
Closest in time.
Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning
David Baidoo-Anu and Leticia Owusu Ansah · 2023
Closest in time.
A Multitask, Multilingual, Multimodal Evaluation of Chatgpt on Reasoning, Hallucination, and Interactivity
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, Quyet V. Do, Yan Xu, and Pascale Fung · 2023
Closest in time.
Sparks of Artificial General Intelligence: Early Experiments with GPT-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott M. Lundberg, Harsha Nori, Hamid Palangi, Marco Túlio Ribeiro, and Yi Zhang · 2023
Closest in time.
Large Language Models Cannot Self-Correct Reasoning Yet
Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, and Denny Zhou · 2023
Closest in time.
Challenges and Applications of Large Language Models
Jean Kaddour, Joshua Harris, Maximilian Mozes, Herbie Bradley, Roberta Raileanu, and Robert McHardy · 2023
Closest in time.
Using Large Language Models to Enhance Programming Error Messages
Juho Leinonen, Arto Hellas, Sami Sarsa, Brent N. Reeves, Paul Denny, James Prather, and Brett A. Becker · 2023
Closest in time.
Generative AI and the Future of Education: Ragnarök or Reformation? A Paradoxical Perspective from Management Educators
Weng Marc Lim, Asanka Gunasekara, Jessica Leigh Pallant, Jason Ian Pallant, and Ekaterina Pechenkina · 2023
Closest in time.
Educational Research and AI-Generated Writing: Confronting the Coming Tsunami
Tamara Tate, Shayan Doroudi, Daniel Ritchie, and Ying Xu · 2023
Closest in time.
Synthesizing a Progression of Subtasks for Block-Based Visual Programming Tasks
Alperen Tercan, Ahana Ghosh, Hasan Ferit Eniser, Maria Christakis, and Adish Singla · 2023
Closest in time.