| Man is to computer programmer as woman is to homemaker? debiasing word embeddings T Bolukbasi, KW Chang, JY Zou, V Saligrama, AT Kalai Advances in neural information processing systems 29, 2016 | 3122 | 2016 |
| The what-if tool: Interactive probing of machine learning models J Wexler, M Pushkarna, T Bolukbasi, M Wattenberg, F Viégas, J Wilson IEEE transactions on visualization and computer graphics 26 (1), 56-65, 2019 | 454 | 2019 |
| Adaptive neural networks for efficient inference T Bolukbasi, J Wang, O Dekel, V Saligrama International Conference on Machine Learning, 527-536, 2017 | 390* | 2017 |
| Xrai: Better attributions through regions A Kapishnikov, T Bolukbasi, F Viégas, M Terry Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 205 | 2019 |
| The language interpretability tool: Extensible, interactive visualizations and analysis for NLP models I Tenney, J Wexler, J Bastings, T Bolukbasi, A Coenen, S Gehrmann, ... arXiv preprint arXiv:2008.05122, 2020 | 138 | 2020 |
| Quantifying and reducing stereotypes in word embeddings T Bolukbasi, KW Chang, J Zou, V Saligrama, A Kalai arXiv preprint arXiv:1606.06121, 2016 | 81 | 2016 |
| Debiasing embeddings for reduced gender bias in text classification F Prost, N Thain, T Bolukbasi arXiv preprint arXiv:1908.02810, 2019 | 58 | 2019 |
| Guided integrated gradients: An adaptive path method for removing noise A Kapishnikov, S Venugopalan, B Avci, B Wedin, M Terry, T Bolukbasi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 52 | 2021 |
| Model selection by linear programming J Wang, T Bolukbasi, K Trapeznikov, V Saligrama Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 35 | 2014 |
| Bing++: A fast high quality object proposal generator at 100fps Z Zhang, Y Liu, T Bolukbasi, MM Cheng, V Saligrama arXiv preprint arXiv:1511.04511 1, 2015 | 27 | 2015 |
| An interpretability illusion for bert T Bolukbasi, A Pearce, A Yuan, A Coenen, E Reif, F Viégas, ... arXiv preprint arXiv:2104.07143, 2021 | 26 | 2021 |
| Tracing knowledge in language models back to the training data E Akyürek, T Bolukbasi, F Liu, B Xiong, I Tenney, J Andreas, K Guu arXiv preprint arXiv:2205.11482, 2022 | 15 | 2022 |
| Towards tracing knowledge in language models back to the training data E Akyürek, T Bolukbasi, F Liu, B Xiong, I Tenney, J Andreas, K Guu Findings of the Association for Computational Linguistics: EMNLP 2022, 2429-2446, 2022 | 12 | 2022 |
| Resource constrained structured prediction T Bolukbasi, KW Chang, J Wang, V Saligrama Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 11 | 2017 |
| Simfluence: Modeling the influence of individual training examples by simulating training runs K Guu, A Webson, E Pavlick, L Dixon, I Tenney, T Bolukbasi arXiv preprint arXiv:2303.08114, 2023 | 5 | 2023 |
| Building a robust text classifier on a test-time budget MR Parvez, T Bolukbasi, KW Chang, V Sarigrama CoRR, abs, 1808 | 4* | 1808 |
| Towards Agile Text Classifiers for Everyone M Mozes, J Hoffmann, K Tomanek, M Kouate, N Thain, A Yuan, ... arXiv preprint arXiv:2302.06541, 2023 | 3 | 2023 |
| Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning M Mozes, T Bolukbasi, A Yuan, F Liu, N Thain, L Dixon arXiv preprint arXiv:2302.06598, 2023 | 2 | 2023 |
| IMACS: Image Model Attribution Comparison Summaries E Schoop, B Wedin, A Kapishnikov, T Bolukbasi, M Terry arXiv preprint arXiv:2201.11196, 2022 | 2 | 2022 |
| Probing ML models for fairness with the what-if tool and SHAP: hands-on tutorial J Wexler, M Pushkarna, S Robinson, T Bolukbasi, A Zaldivar Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020 | 2 | 2020 |
Venkatesh SaligramaProfessor, Electrical and Computer Engineering, Boston UniversityVerified email at bu.edu
