Tolga Bolukbasi

According to our database, Tolga Bolukbasi authored at least 27 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Scalable Influence and Fact Tracing for Large Language Model Pretraining.

Tyler A. Chang, Dheeraj Rajagopal, Tolga Bolukbasi, Lucas Dixon, Ian Tenney

CoRR, 2024

2023

Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs.

Kelvin Guu, Albert Webson, Ellie Pavlick, Lucas Dixon, Ian Tenney, Tolga Bolukbasi

CoRR, 2023

Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning.

Maximilian Mozes, Tolga Bolukbasi, Ann Yuan, Frederick Liu, Nithum Thain, Lucas Dixon

CoRR, 2023

Self-Influence Guided Data Reweighting for Language Model Pre-training.

Megh Thakkar, Tolga Bolukbasi, Sriram Ganapathy, Shikhar Vashishth, Sarath Chandar, Partha Talukdar

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Towards Agile Text Classifiers for Everyone.

Maximilian Mozes, Jessica Hoffmann, Katrin Tomanek, Muhamed Kouate, Nithum Thain, Ann Yuan, Tolga Bolukbasi, Lucas Dixon

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Tracing Knowledge in Language Models Back to the Training Data.

Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu

CoRR, 2022

IMACS: Image Model Attribution Comparison Summaries.

Eldon Schoop, Ben Wedin, Andrei Kapishnikov, Tolga Bolukbasi, Michael Terry

CoRR, 2022

Towards Tracing Knowledge in Language Models Back to the Training Data.

Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

An Interpretability Illusion for BERT.

Tolga Bolukbasi, Adam Pearce, Ann Yuan, Andy Coenen, Emily Reif, Fernanda B. Viégas, Martin Wattenberg

CoRR, 2021

Guided Integrated Gradients: An Adaptive Path Method for Removing Noise.

Andrei Kapishnikov, Subhashini Venugopalan, Besim Avci, Ben Wedin, Michael Terry, Tolga Bolukbasi

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

The What-If Tool: Interactive Probing of Machine Learning Models.

James Wexler, Mahima Pushkarna, Tolga Bolukbasi, Martin Wattenberg, Fernanda B. Viégas, Jimbo Wilson

IEEE Trans. Vis. Comput. Graph., 2020

Probing ML models for fairness with the what-if tool and SHAP: hands-on tutorial.

James Wexler, Mahima Pushkarna, Sara Robinson, Tolga Bolukbasi, Andrew Zaldivar

Proceedings of the FAT* '20: Conference on Fairness, 2020

The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models.

Ian Tenney, James Wexler, Jasmijn Bastings, Tolga Bolukbasi, Andy Coenen, Sebastian Gehrmann, Ellen Jiang, Mahima Pushkarna, Carey Radebaugh, Emily Reif, Ann Yuan

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2020

2019

Debiasing Embeddings for Reduced Gender Bias in Text Classification.

Flavien Prost, Nithum Thain, Tolga Bolukbasi

CoRR, 2019

Segment Integrated Gradients: Better attributions through regions.

Andrei Kapishnikov, Tolga Bolukbasi, Fernanda B. Viégas, Michael Terry

CoRR, 2019

XRAI: Better Attributions Through Regions.

Andrei Kapishnikov, Tolga Bolukbasi, Fernanda B. Viégas, Michael Terry

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Robust Text Classifier on Test-Time Budgets.

Md. Rizwan Parvez, Tolga Bolukbasi, Kai-Wei Chang, Venkatesh Saligrama

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

Building a Robust Text Classifier on a Test-Time Budget.

Md. Rizwan Parvez, Tolga Bolukbasi, Kai-Wei Chang, Venkatesh Sarigrama

CoRR, 2018

Zero-Shot Detection.

Pengkai Zhu, Hanxiao Wang, Tolga Bolukbasi, Venkatesh Saligrama

CoRR, 2018

2017

Adaptive Neural Networks for Fast Test-Time Prediction.

Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama

CoRR, 2017

Adaptive Neural Networks for Efficient Inference.

Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama

Proceedings of the 34th International Conference on Machine Learning, 2017

Resource Constrained Structured Prediction.

Tolga Bolukbasi, Kai-Wei Chang, Joseph Wang, Venkatesh Saligrama

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Quantifying and Reducing Stereotypes in Word Embeddings.

Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai

CoRR, 2016

Structured Prediction with Test-time Budget Constraints.

Tolga Bolukbasi, Kai-Wei Chang, Joseph Wang, Venkatesh Saligrama

CoRR, 2016

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings.

Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

BING++: A Fast High Quality Object Proposal Generator at 100fps.

Ziming Zhang, Yun Liu, Tolga Bolukbasi, Ming-Ming Cheng, Venkatesh Saligrama

CoRR, 2015

2014

Model Selection by Linear Programming.

Joseph Wang, Tolga Bolukbasi, Kirill Trapeznikov, Venkatesh Saligrama

Proceedings of the Computer Vision - ECCV 2014, 2014