Ben Hutchinson

55 papers A* 6A 1B 1C 2Misc 1Journal 29Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	'I have to talk proper white ways': Australian Aboriginal English Speakers' Experiences with Voice Technologies. CHI Extended Abstracts Celeste Rodríguez Louro, Glenys Dale Collard, Hope Narrier, Katrina Cox, Lily Hayward, Daniel Colbung, Ben Hutchinson
2025	—	`conf`	Designing Speech Technologies for Australian Aboriginal English: Opportunities, Risks and Participation. FAccT Ben Hutchinson, Celeste Rodríguez Louro, Glenys Collard, Ned Cooper
2025	J	`jnl`	Designing Speech Technologies for Australian Aboriginal English: Opportunities, Risks and Participation. CoRR Ben Hutchinson, Celeste Rodríguez Louro, Glenys Collard, Ned Cooper
2024	—	`conf`	"It's how you do things that matters": Attending to Process to Better Serve Indigenous Communities with Language Technologies. EACL (2) Ned Cooper, Courtney Heldreth, Ben Hutchinson
2024	J	`jnl`	"It's how you do things that matters": Attending to Process to Better Serve Indigenous Communities with Language Technologies. CoRR Ned Cooper, Courtney Heldreth, Ben Hutchinson
2024	J	`jnl`	Modeling the Sacred: Considerations when Using Considerations when Using Religious Texts in Natural Language Processing. CoRR Ben Hutchinson
2024	—	`conf`	Modeling the Sacred: Considerations when Using Religious Texts in Natural Language Processing. NAACL-HLT (Findings) Ben Hutchinson
2024	J	`jnl`	Socially Responsible Data for Large Multilingual Language Models. CoRR Andrew Smart, Ben Hutchinson, Lameck Mbangula Amugongo, Suzanne Dikker, Alex Zito, Amber Ebinama, Zara Wudiri, Ding Wang, Erin van Liemt, João Sedoc, Seyi Olojo, Stanley Uwakwe, Edem Wornyo, Sonja Schmer-Galunder, Jamila Smith-Loud
2024	J	`jnl`	Troubling Taxonomies in GenAI Evaluation. CoRR Glen Berman, Ned Cooper, Wesley Hanwen Deng, Ben Hutchinson
2023	J	`jnl`	PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel
2022	J	`jnl`	Cultural Incongruencies in Artificial Intelligence. CoRR Vinodkumar Prabhakaran, Rida Qadri, Ben Hutchinson
2022	—	`conf`	Evaluation Gaps in Machine Learning Practice. FAccT Ben Hutchinson, Negar Rostamzadeh, Christina Greer, Katherine A. Heller, Vinodkumar Prabhakaran
2022	J	`jnl`	Evaluation Gaps in Machine Learning Practice. CoRR Ben Hutchinson, Negar Rostamzadeh, Christina Greer, Katherine A. Heller, Vinodkumar Prabhakaran
2022	J	`jnl`	LaMDA: Language Models for Dialog Applications. CoRR Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, Yaguang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Kathleen S. Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Agüera y Arcas, Claire Cui, Marian Croak, Ed H. Chi, Quoc Le
2022	J	`jnl`	PaLM: Scaling Language Modeling with Pathways. CoRR Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel
2022	J	`jnl`	Scaling Autoregressive Models for Content-Rich Text-to-Image Generation. CoRR Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, Yonghui Wu
2022	J	`jnl`	Scaling Autoregressive Models for Content-Rich Text-to-Image Generation. Trans. Mach. Learn. Res. Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, Yonghui Wu
2022	—	`conf`	Underspecification in Scene Description-to-Depiction Tasks. AACL/IJCNLP (1) Ben Hutchinson, Jason Baldridge, Vinodkumar Prabhakaran
2022	J	`jnl`	Underspecification in Scene Description-to-Depiction Tasks. CoRR Ben Hutchinson, Jason Baldridge, Vinodkumar Prabhakaran
2021	J	`jnl`	Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
2021	—	`conf`	Re-imagining Algorithmic Fairness in India and Beyond. FAccT Nithya Sambasivan, Erin Arnesen, Ben Hutchinson, Tulsee Doshi, Vinodkumar Prabhakaran
2021	J	`jnl`	Re-imagining Algorithmic Fairness in India and Beyond. CoRR Nithya Sambasivan, Erin Arnesen, Ben Hutchinson, Tulsee Doshi, Vinodkumar Prabhakaran
2021	J	`jnl`	Thinking Beyond Distributions in Testing Machine Learned Models. CoRR Negar Rostamzadeh, Ben Hutchinson, Christina Greer, Vinodkumar Prabhakaran
2021	—	`conf`	Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure. FAccT Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, Margaret Mitchell
2020	J	`jnl`	Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing. CoRR Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes
2020	—	`conf`	Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing. FAT* Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes
2020	C	`conf`	Diversity and Inclusion Metrics in Subset Selection. AIES Margaret Mitchell, Dylan K. Baker, Nyalleng Moorosi, Emily Denton, Ben Hutchinson, Alex Hanna, Timnit Gebru, Jamie Morgenstern
2020	J	`jnl`	Diversity and Inclusion Metrics in Subset Selection. CoRR Margaret Mitchell, Dylan K. Baker, Nyalleng Moorosi, Emily Denton, Ben Hutchinson, Alex Hanna, Timnit Gebru, Jamie Morgenstern
2020	J	`jnl`	Fairness Preferences, Actual and Hypothetical: A Study of Crowdworker Incentives. CoRR Angie Peng, Jeff Naecker, Ben Hutchinson, Andrew Smart, Nyalleng Moorosi
2020	J	`jnl`	Non-portability of Algorithmic Fairness in India. CoRR Nithya Sambasivan, Erin Arnesen, Ben Hutchinson, Vinodkumar Prabhakaran
2020	A*	`conf`	Social Biases in NLP Models as Barriers for Persons with Disabilities. ACL Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, Stephen Denuyl
2020	J	`jnl`	Social Biases in NLP Models as Barriers for Persons with Disabilities. CoRR Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, Stephen Denuyl
2020	J	`jnl`	Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure. CoRR Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, Margaret Mitchell
2020	J	`jnl`	Unintended machine learning biases as social barriers for persons with disabilitiess. ACM SIGACCESS Access. Comput. Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, Stephen Denuyl
2020	C	`conf`	Why Reliabilism Is not Enough: Epistemic and Moral Justification in Machine Learning. AIES Andrew Smart, Larry James, Ben Hutchinson, Simone Wu, Shannon Vallor
2019	—	`conf`	50 Years of Test (Un)fairness: Lessons for Machine Learning. FAT Ben Hutchinson, Margaret Mitchell
2019	J	`jnl`	Advances and Open Problems in Federated Learning. CoRR Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
2019	J	`jnl`	Detecting Bias with Generative Counterfactual Face Attribute Augmentation. CoRR Emily Denton, Ben Hutchinson, Margaret Mitchell, Timnit Gebru
2019	A*	`conf`	Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned. KDD Sarah Bird, Ben Hutchinson, Krishnaram Kenthapadi, Emre Kiciman, Margaret Mitchell
2019	—	`conf`	Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned. WWW (Companion Volume) Sarah Bird, Ben Hutchinson, Krishnaram Kenthapadi, Emre Kiciman, Margaret Mitchell
2019	J	`jnl`	Interpreting Social Respect: A Normative Lens for ML Models. CoRR Ben Hutchinson, K. J. Pittl, Margaret Mitchell
2019	—	`conf`	Model Cards for Model Reporting. FAT Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru
2019	—	`conf`	Perturbation Sensitivity Analysis to Detect Unintended Model Biases. EMNLP/IJCNLP (1) Vinodkumar Prabhakaran, Ben Hutchinson, Margaret Mitchell
2019	J	`jnl`	Perturbation Sensitivity Analysis to Detect Unintended Model Biases. CoRR Vinodkumar Prabhakaran, Ben Hutchinson, Margaret Mitchell
2018	J	`jnl`	50 Years of Test (Un)fairness: Lessons for Machine Learning. CoRR Ben Hutchinson, Margaret Mitchell
2018	J	`jnl`	Model Cards for Model Reporting. CoRR Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru
2009	A*	`conf`	Using the Web for Language Independent Spellchecking and Autocorrection. EMNLP Casey Whitelaw, Ben Hutchinson, Grace Chung, Ged Ellis
2007	Misc	`conf`	TAT: An Author Profiling Tool with Application to Arabic Emails. ALTA Dominique Estival, Tanja Gaustad, Son Bao Pham, Will Radford, Ben Hutchinson
2005	A*	`conf`	MDL-based Acquisition of Substitutability Relationships between Discourse Connectives. IJCAI Ben Hutchinson
2005	A*	`conf`	Modelling the Substitutability of Discourse Connectives. ACL Ben Hutchinson
2005	—	`—`	The automatic acquisition of knowledge about discourse connectives. Ben Hutchinson
2004	A*	`conf`	Acquiring the Meaning of Discourse Markers. ACL Ben Hutchinson
2004	B	`conf`	Mining the Web for Discourse Markers. LREC Ben Hutchinson
2001	A	`conf`	A functional approach to speech recognition evaluation. INTERSPEECH Ben Hutchinson
2001	—	`conf`	Um, one large pizza. A preliminary study of disfluency modelling for improving ASR. DiSS Ben Hutchinson, Cécile Pereira