| Avlnet: Learning audio-visual language representations from instructional videos A Rouditchenko, A Boggust, D Harwath, B Chen, D Joshi, S Thomas, ... arXiv preprint arXiv:2006.09199, 2020 | 147 | 2020 |
| Multimodal clustering networks for self-supervised learning from unlabeled videos B Chen, A Rouditchenko, K Duarte, H Kuehne, S Thomas, A Boggust, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 93 | 2021 |
| Embedding comparator: Visualizing differences in global structure and local neighborhoods via small multiples A Boggust, B Carter, A Satyanarayan Proceedings of the 27th International Conference on Intelligent User …, 2022 | 63 | 2022 |
| Shared interest: Measuring human-ai alignment to identify recurring patterns in model behavior A Boggust, B Hoover, A Satyanarayan, H Strobelt Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems …, 2022 | 48 | 2022 |
| Vistext: A benchmark for semantically rich chart captioning BJ Tang, A Boggust, A Satyanarayan arXiv preprint arXiv:2307.05356, 2023 | 45 | 2023 |
| Grounding spoken words in unlabeled video. AW Boggust, K Audhkhasi, D Joshi, D Harwath, S Thomas, RS Feris, ... CVPR Workshops 2, 17, 2019 | 25 | 2019 |
| Saliency Cards: A Framework to Characterize and Compare Saliency Methods A Boggust, H Suresh, H Strobelt, J Guttag, A Satyanarayan Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 9* | 2023 |
| Cascaded multilingual audio-visual learning from videos A Rouditchenko, A Boggust, D Harwath, S Thomas, H Kuehne, B Chen, ... arXiv preprint arXiv:2111.04823, 2021 | 6 | 2021 |
| LeGrad: An Explainability Method for Vision Transformers via Feature Formation Sensitivity W Bousselham, A Boggust, S Chaybouti, H Strobelt, H Kuehne arXiv preprint arXiv:2404.03214, 2024 | 2 | 2024 |
| What is a Fair Diffusion Model? Designing Generative Text-To-Image Models to Incorporate Various Worldviews Z De Simone, A Boggust, A Satyanarayan, A Wilson arXiv preprint arXiv:2309.09944, 2023 | 1 | 2023 |
| Compress and Compare: Interactively Evaluating Efficiency and Behavior Across ML Model Compression Experiments A Boggust, V Sivaraman, Y Assogba, D Ren, D Moritz, F Hohman IEEE Transactions on Visualization and Computer Graphics, 2024 | | 2024 |
| Abstraction Alignment: Comparing Model and Human Conceptual Relationships A Boggust, H Bang, H Strobelt, A Satyanarayan arXiv preprint arXiv:2407.12543, 2024 | | 2024 |
| Shared Interest: Human Annotations vs. AI Saliency A Boggust, B Hoover, A Satyanarayan, H Strobelt Annual Conference on Neural Information Processing Systems, 2020 | | 2020 |
| Unsupervised audio-visual learning in the wild AW Boggust Massachusetts Institute of Technology, 2020 | | 2020 |
| Explanation Alignment: Quantifying the Correctness of Model Reasoning At Scale H Bang, A Boggust, A Satyanarayan | | |
| Interpreting Uncertainty: Understanding Neural Network Decisions with Conceptual Hierarchies A Boggust, A Satyanarayan, H Strobelt | | |
