| Large language models still can't plan (a benchmark for LLMs on planning and reasoning about change) K Valmeekam, A Olmo, S Sreedharan, S Kambhampati NeurIPS 2022 Foundation Models for Decision Making Workshop, 2022 | 352 | 2022 |
| Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change K Valmeekam, M Marquez, A Olmo, S Sreedharan, S Kambhampati Advances in Neural Information Processing Systems 36, 38975-38987, 2023 | 168 | 2023 |
| Imperfect ImaGANation: Implications of GANs exacerbating biases on facial data augmentation and snapchat face lenses N Jain, A Olmo, S Sengupta, L Manikonda, S Kambhampati Artificial Intelligence 304, 103652, 2022 | 96* | 2022 |
| On the planning abilities of large language models (a critical investigation with a proposed benchmark) K Valmeekam, S Sreedharan, M Marquez, A Olmo, S Kambhampati arXiv preprint arXiv:2302.06706, 2023 | 81 | 2023 |
| GPT3-to-plan: Extracting plans from text using GPT-3 A Olmo, S Sreedharan, S Kambhampati arXiv preprint arXiv:2106.07131, 2021 | 70 | 2021 |
| Model-free model reconciliation S Sreedharan, A Olmo, AP Mishra, S Kambhampati arXiv preprint arXiv:1903.07198, 2019 | 40 | 2019 |
| Towards understanding user preferences for explanation types in model reconciliation Z Zahedi, A Olmo, T Chakraborti, S Sreedharan, S Kambhampati 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2019 | 28 | 2019 |
| Not all failure modes are created equal: Training deep neural networks for explicable (mis) classification A Olmo, S Sengupta, S Kambhampati arXiv preprint arXiv:2006.14841, 2020 | 8 | 2020 |
| Physics-driven convolutional autoencoder approach for CFD data compressions A Olmo, A Zamzam, A Glaws, R King arXiv preprint arXiv:2210.09262, 2022 | 6 | 2022 |
| Analyzing Failure Modes of Inscrutable Machine Learning Models AO Hernandez Arizona State University, 2022 | | 2022 |
| Extensió del Plugin de Sintonització de Paràmetres MPI de l'eina PTF A Olmo Hernández | | |
| Autoregressive Density Estimation in Latent Spaces A Olmo Hernández University of Colorado Colorado Springs. Kraemer Family Library, 0 | | |
Subbarao KambhampatiArizona State Universityایمیل تأیید شده در asu.edu