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ORCIDTolga Bolukbasi
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2020 – today
- 2023
[c12]Maximilian Mozes, Jessica Hoffmann, Katrin Tomanek, Muhamed Kouate, Nithum Thain, Ann Yuan, Tolga Bolukbasi, Lucas Dixon:
Towards Agile Text Classifiers for Everyone. EMNLP (Findings) 2023: 400-414- [c11]Megh Thakkar, Tolga Bolukbasi, Sriram Ganapathy, Shikhar Vashishth, Sarath Chandar, Partha Talukdar:
Self-Influence Guided Data Reweighting for Language Model Pre-training. EMNLP 2023: 2033-2045 - [i19]Maximilian Mozes, Jessica Hoffmann, Katrin Tomanek, Muhamed Kouate, Nithum Thain, Ann Yuan, Tolga Bolukbasi, Lucas Dixon:
Towards Agile Text Classifiers for Everyone. CoRR abs/2302.06541 (2023) - [i18]Maximilian Mozes, Tolga Bolukbasi, Ann Yuan, Frederick Liu, Nithum Thain, Lucas Dixon:
Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning. CoRR abs/2302.06598 (2023) - [i17]Kelvin Guu, Albert Webson, Ellie Pavlick, Lucas Dixon, Ian Tenney, Tolga Bolukbasi:
Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs. CoRR abs/2303.08114 (2023) - [i16]Megh Thakkar, Tolga Bolukbasi, Sriram Ganapathy, Shikhar Vashishth, Sarath Chandar, Partha Talukdar:
Self-Influence Guided Data Reweighting for Language Model Pre-training. CoRR abs/2311.00913 (2023) - 2022
- [c10]Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu:
Towards Tracing Knowledge in Language Models Back to the Training Data. EMNLP (Findings) 2022: 2429-2446 - [i15]Eldon Schoop, Ben Wedin, Andrei Kapishnikov, Tolga Bolukbasi, Michael Terry:
IMACS: Image Model Attribution Comparison Summaries. CoRR abs/2201.11196 (2022) - [i14]Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu:
Tracing Knowledge in Language Models Back to the Training Data. CoRR abs/2205.11482 (2022) - 2021
- [c9]Andrei Kapishnikov, Subhashini Venugopalan, Besim Avci, Ben Wedin, Michael Terry, Tolga Bolukbasi:
Guided Integrated Gradients: An Adaptive Path Method for Removing Noise. CVPR 2021: 5050-5058 - [i13]Tolga Bolukbasi, Adam Pearce, Ann Yuan, Andy Coenen, Emily Reif, Fernanda B. Viégas, Martin Wattenberg:
An Interpretability Illusion for BERT. CoRR abs/2104.07143 (2021) - [i12]Andrei Kapishnikov, Subhashini Venugopalan, Besim Avci, Ben Wedin, Michael Terry, Tolga Bolukbasi:
Guided Integrated Gradients: An Adaptive Path Method for Removing Noise. CoRR abs/2106.09788 (2021) - 2020
- [j1]James Wexler, Mahima Pushkarna, Tolga Bolukbasi, Martin Wattenberg, Fernanda B. Viégas, Jimbo Wilson:
The What-If Tool: Interactive Probing of Machine Learning Models. IEEE Trans. Vis. Comput. Graph. 26(1): 56-65 (2020) - [c8]Ian Tenney, James Wexler, Jasmijn Bastings, Tolga Bolukbasi, Andy Coenen, Sebastian Gehrmann, Ellen Jiang, Mahima Pushkarna, Carey Radebaugh, Emily Reif, Ann Yuan:
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models. EMNLP (Demos) 2020: 107-118 - [c7]James Wexler, Mahima Pushkarna, Sara Robinson, Tolga Bolukbasi, Andrew Zaldivar:
Probing ML models for fairness with the what-if tool and SHAP: hands-on tutorial. FAT* 2020: 705 - [i11]Ian Tenney, James Wexler, Jasmijn Bastings, Tolga Bolukbasi, Andy Coenen, Sebastian Gehrmann, Ellen Jiang, Mahima Pushkarna, Carey Radebaugh, Emily Reif, Ann Yuan:
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models. CoRR abs/2008.05122 (2020)
2010 – 2019
- 2019
- [c6]Md. Rizwan Parvez, Tolga Bolukbasi, Kai-Wei Chang, Venkatesh Saligrama:
Robust Text Classifier on Test-Time Budgets. EMNLP/IJCNLP (1) 2019: 1167-1172 - [c5]Andrei Kapishnikov, Tolga Bolukbasi, Fernanda B. Viégas, Michael Terry:
XRAI: Better Attributions Through Regions. ICCV 2019: 4947-4956 - [i10]Andrei Kapishnikov, Tolga Bolukbasi, Fernanda B. Viégas, Michael Terry:
Segment Integrated Gradients: Better attributions through regions. CoRR abs/1906.02825 (2019) - [i9]James Wexler, Mahima Pushkarna, Tolga Bolukbasi, Martin Wattenberg, Fernanda B. Viégas, Jimbo Wilson:
The What-If Tool: Interactive Probing of Machine Learning Models. CoRR abs/1907.04135 (2019) - [i8]Flavien Prost, Nithum Thain, Tolga Bolukbasi:
Debiasing Embeddings for Reduced Gender Bias in Text Classification. CoRR abs/1908.02810 (2019) - 2018
- [i7]Pengkai Zhu, Hanxiao Wang, Tolga Bolukbasi, Venkatesh Saligrama:
Zero-Shot Detection. CoRR abs/1803.07113 (2018) - [i6]Md. Rizwan Parvez, Tolga Bolukbasi, Kai-Wei Chang, Venkatesh Sarigrama:
Building a Robust Text Classifier on a Test-Time Budget. CoRR abs/1808.08270 (2018) - 2017
- [c4]Tolga Bolukbasi, Kai-Wei Chang, Joseph Wang, Venkatesh Saligrama
:
Resource Constrained Structured Prediction. AAAI 2017: 1756-1762 - [c3]Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama:
Adaptive Neural Networks for Efficient Inference. ICML 2017: 527-536 - [i5]Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama:
Adaptive Neural Networks for Fast Test-Time Prediction. CoRR abs/1702.07811 (2017) - 2016
- [c2]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai:
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. NIPS 2016: 4349-4357 - [i4]Tolga Bolukbasi, Kai-Wei Chang, Joseph Wang, Venkatesh Saligrama:
Structured Prediction with Test-time Budget Constraints. CoRR abs/1602.08761 (2016) - [i3]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai:
Quantifying and Reducing Stereotypes in Word Embeddings. CoRR abs/1606.06121 (2016) - [i2]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Kalai:
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. CoRR abs/1607.06520 (2016) - 2015
- [i1]Ziming Zhang, Yun Liu, Tolga Bolukbasi, Ming-Ming Cheng, Venkatesh Saligrama:
BING++: A Fast High Quality Object Proposal Generator at 100fps. CoRR abs/1511.04511 (2015) - 2014
- [c1]Joseph Wang, Tolga Bolukbasi, Kirill Trapeznikov, Venkatesh Saligrama:
Model Selection by Linear Programming. ECCV (2) 2014: 647-662
Coauthor Index
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