| Reader: Model-based language-instructed reinforcement learning N Dainese, P Marttinen, A Ilin Conference on Empirical Methods in Natural Language Processing, 16583-16599, 2023 | 1 | 2023 |
| Benchmarking Educational Program Repair C Koutcheme, N Dainese, S Sarsa, J Leinonen, A Hellas, P Denny Evaluation 3, 4, 0 | 1 | |
| Open Source Language Models Can Provide Feedback: Evaluating LLMs' Ability to Help Students Using GPT-4-As-A-Judge C Koutcheme, N Dainese, S Sarsa, A Hellas, J Leinonen, P Denny arXiv preprint arXiv:2405.05253, 2024 | | 2024 |
| In-Context Symbolic Regression: Leveraging Language Models for Function Discovery M Merler, N Dainese, K Haitsiukevich arXiv preprint arXiv:2404.19094, 2024 | | 2024 |
| Can docstring reformulation with an LLM improve code generation? N Dainese, A Ilin, P Marttinen Proceedings of the 18th Conference of the European Chapter of the …, 2024 | | 2024 |
| Deep Reinforcement Learning methods for StarCraft II Learning Environment N Dainese | | 2020 |
