| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 724 | 2022 |
| Nl-augmenter: A framework for task-sensitive natural language augmentation KD Dhole, V Gangal, S Gehrmann, A Gupta, Z Li, S Mahamood, ... arXiv preprint arXiv:2112.02721, 2021 | 64 | 2021 |
| Fabrice Harel-Canada, Antoine Honore, Ishan Jindal, Przemyslaw K KD Dhole, V Gangal, S Gehrmann, A Gupta, Z Li, S Mahamood, ... Joniak, Denis Kleyko, Venelin Kovatchev, and et al, 2021 | 16 | 2021 |
| Automatic question generation for scaffolding self-explanations for code comprehension LJ Tamang, R Banjade, J Chapagain, V Rus International Conference on Artificial Intelligence in Education, 743-748, 2022 | 9 | 2022 |
| Domain model discovery from textbooks for computer programming intelligent tutors R Banjade The International FLAIRS Conference Proceedings, 34., 2021 | 6 | 2021 |
| Improving code comprehension through scaffolded self-explanations P Oli, R Banjade, AB Lekshmi Narayanan, J Chapagain, LJ Tamang, ... International Conference on Artificial Intelligence in Education, 478-483, 2023 | 3 | 2023 |
| Preliminary experiments with transformer based approaches to automatically inferring domain models from textbooks R Banjade, P Oli, LJ Tamang, V Rus Proceedings of the 15th International Conference on Educational Data Mining, 2022 | 2 | 2022 |
| The Behavior of Large Language Models When Prompted to Generate Code Explanations Priti Oli, Rabin Banjade, Vasile Rus, Jeevan Chapagain NeurIPS'23 Workshop on Generative AI for Education (GAIED), 2023 | 1* | 2023 |
| Automated Assessment of Student Self-explanation During Source Code Comprehension J Chapagain, L Tamang The International FLAIRS Conference Proceedings 35, 2022 | 1 | 2022 |
| Automated Assessment of Quality of Jupyter Notebooks Using Artificial Intelligence and Big Code P Oli, R Banjade, LJ Tamang, V Rus The International FLAIRS Conference Proceedings 34, 2021 | 1 | 2021 |
| Explaining Code Examples in Introductory Programming Courses: LLM vs Humans ABL Narayanan, P Oli, J Chapagain, M Hassany, R Banjade, ... EasyChair, 2024 | | 2024 |
| Automated Assessment of Students' Code Comprehension using LLMs P Oli, R Banjade, J Chapagain, V Rus arXiv preprint arXiv:2401.05399, 2023 | | 2023 |
| Explaining code examples in introductory programming courses: Llm vs humans P Brusilovsky, AB Lekshmi-Narayanan, P Oli, J Chapagain, M Hassany, ... arXiv preprint arXiv:2403.05538, 2023 | | 2023 |
| Automated Extraction of Domain Models from Textbook Indexes for Developing Intelligent Tutoring Systems R Banjade, P Oli, V Rus International Conference on Intelligent Tutoring Systems, 124-136, 2023 | | 2023 |
| Check for updates Automated Extraction of Domain Models from Textbook Indexes for Developing Intelligent Tutoring Systems R Banjade, P Oli, V Rus Augmented Intelligence and Intelligent Tutoring Systems: 19th International …, 2023 | | 2023 |
| SelfCode: An Annotated Corpus and a Model for Automated Assessment of Self-explanation during Source Code Comprehension J Chapagain, Z Risha, R Banjade, P Oli, L Tamang, P Brusilovsky, V Rus The International FLAIRS Conference Proceedings 36, 2023 | | 2023 |
| When is Reading More Effective than Tutoring? An Analysis Through the Lens of Students' Self-Efficacy among Novices in Computer Science P Oli, R Banjade, AB Narayanan, P Brusilovsky, V Rus Proceedings of 7th Educational Data Mining in Computer Science Education …, 2023 | | 2023 |
Vasile RusThe University of MemphisVerified email at memphis.edu
