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Ben Hutchinson
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2020 – today
- 2024
- [c23]Ned Cooper, Courtney Heldreth, Ben Hutchinson:
"It's how you do things that matters": Attending to Process to Better Serve Indigenous Communities with Language Technologies. EACL (2) 2024: 204-211 - [c22]Ben Hutchinson:
Modeling the Sacred: Considerations when Using Religious Texts in Natural Language Processing. NAACL-HLT (Findings) 2024: 1029-1043 - [i23]Ned Cooper, Courtney Heldreth, Ben Hutchinson:
"It's how you do things that matters": Attending to Process to Better Serve Indigenous Communities with Language Technologies. CoRR abs/2402.02639 (2024) - [i22]Ben Hutchinson:
Modeling the Sacred: Considerations when Using Considerations when Using Religious Texts in Natural Language Processing. CoRR abs/2404.14740 (2024) - [i21]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:
Socially Responsible Data for Large Multilingual Language Models. CoRR abs/2409.05247 (2024) - 2023
- [j4]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:
PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. 24: 240:1-240:113 (2023) - 2022
- [j3]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:
Scaling Autoregressive Models for Content-Rich Text-to-Image Generation. Trans. Mach. Learn. Res. 2022 (2022) - [c21]Ben Hutchinson, Negar Rostamzadeh, Christina Greer, Katherine A. Heller, Vinodkumar Prabhakaran:
Evaluation Gaps in Machine Learning Practice. FAccT 2022: 1859-1876 - [c20]Ben Hutchinson, Jason Baldridge, Vinodkumar Prabhakaran:
Underspecification in Scene Description-to-Depiction Tasks. AACL/IJCNLP (1) 2022: 1172-1184 - [i20]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:
LaMDA: Language Models for Dialog Applications. CoRR abs/2201.08239 (2022) - [i19]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:
PaLM: Scaling Language Modeling with Pathways. CoRR abs/2204.02311 (2022) - [i18]Ben Hutchinson, Negar Rostamzadeh, Christina Greer, Katherine A. Heller, Vinodkumar Prabhakaran:
Evaluation Gaps in Machine Learning Practice. CoRR abs/2205.05256 (2022) - [i17]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:
Scaling Autoregressive Models for Content-Rich Text-to-Image Generation. CoRR abs/2206.10789 (2022) - [i16]Ben Hutchinson, Jason Baldridge, Vinodkumar Prabhakaran:
Underspecification in Scene Description-to-Depiction Tasks. CoRR abs/2210.05815 (2022) - [i15]Vinodkumar Prabhakaran, Rida Qadri, Ben Hutchinson:
Cultural Incongruencies in Artificial Intelligence. CoRR abs/2211.13069 (2022) - 2021
- [j2]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis
, Arjun Nitin Bhagoji
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [c19]Nithya Sambasivan, Erin Arnesen, Ben Hutchinson, Tulsee Doshi, Vinodkumar Prabhakaran:
Re-imagining Algorithmic Fairness in India and Beyond. FAccT 2021: 315-328 - [c18]Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, Margaret Mitchell:
Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure. FAccT 2021: 560-575 - [i14]Nithya Sambasivan, Erin Arnesen, Ben Hutchinson, Tulsee Doshi, Vinodkumar Prabhakaran:
Re-imagining Algorithmic Fairness in India and Beyond. CoRR abs/2101.09995 (2021) - [i13]Negar Rostamzadeh, Ben Hutchinson, Christina Greer, Vinodkumar Prabhakaran:
Thinking Beyond Distributions in Testing Machine Learned Models. CoRR abs/2112.03057 (2021) - 2020
- [j1]Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, Stephen Denuyl:
Unintended machine learning biases as social barriers for persons with disabilitiess. ACM SIGACCESS Access. Comput. 125: 9 (2020) - [c17]Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, Stephen Denuyl:
Social Biases in NLP Models as Barriers for Persons with Disabilities. ACL 2020: 5491-5501 - [c16]Margaret Mitchell, Dylan K. Baker, Nyalleng Moorosi, Emily Denton, Ben Hutchinson, Alex Hanna, Timnit Gebru, Jamie Morgenstern:
Diversity and Inclusion Metrics in Subset Selection. AIES 2020: 117-123 - [c15]Andrew Smart, Larry James, Ben Hutchinson, Simone Wu, Shannon Vallor
Why Reliabilism Is not Enough: Epistemic and Moral Justification in Machine Learning. AIES 2020: 372-377 - [c14]Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron
Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing. FAT* 2020: 33-44 - [i12]Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes:
Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing. CoRR abs/2001.00973 (2020) - [i11]Margaret Mitchell, Dylan K. Baker, Nyalleng Moorosi, Emily Denton, Ben Hutchinson, Alex Hanna, Timnit Gebru, Jamie Morgenstern:
Diversity and Inclusion Metrics in Subset Selection. CoRR abs/2002.03256 (2020) - [i10]Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, Stephen Denuyl:
Social Biases in NLP Models as Barriers for Persons with Disabilities. CoRR abs/2005.00813 (2020) - [i9]Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, Margaret Mitchell:
Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure. CoRR abs/2010.13561 (2020) - [i8]Nithya Sambasivan, Erin Arnesen, Ben Hutchinson, Vinodkumar Prabhakaran:
Non-portability of Algorithmic Fairness in India. CoRR abs/2012.03659 (2020) - [i7]Angie Peng, Jeff Naecker, Ben Hutchinson, Andrew Smart, Nyalleng Moorosi:
Fairness Preferences, Actual and Hypothetical: A Study of Crowdworker Incentives. CoRR abs/2012.04216 (2020)
2010 – 2019
- 2019
- [c13]Vinodkumar Prabhakaran, Ben Hutchinson, Margaret Mitchell:
Perturbation Sensitivity Analysis to Detect Unintended Model Biases. EMNLP/IJCNLP (1) 2019: 5739-5744 - [c12]Ben Hutchinson, Margaret Mitchell:
50 Years of Test (Un)fairness: Lessons for Machine Learning. FAT 2019: 49-58 - [c11]Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru:
Model Cards for Model Reporting. FAT 2019: 220-229 - [c10]Sarah Bird, Ben Hutchinson, Krishnaram Kenthapadi, Emre Kiciman, Margaret Mitchell:
Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned. KDD 2019: 3205-3206 - [c9]Sarah Bird, Ben Hutchinson, Krishnaram Kenthapadi, Emre Kiciman, Margaret Mitchell:
Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned. WWW (Companion Volume) 2019: 1297-1298 - [i6]Emily Denton, Ben Hutchinson, Margaret Mitchell, Timnit Gebru:
Detecting Bias with Generative Counterfactual Face Attribute Augmentation. CoRR abs/1906.06439 (2019) - [i5]Ben Hutchinson, K. J. Pittl, Margaret Mitchell:
Interpreting Social Respect: A Normative Lens for ML Models. CoRR abs/1908.07336 (2019) - [i4]Vinodkumar Prabhakaran, Ben Hutchinson, Margaret Mitchell:
Perturbation Sensitivity Analysis to Detect Unintended Model Biases. CoRR abs/1910.04210 (2019) - [i3]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
Advances and Open Problems in Federated Learning. CoRR abs/1912.04977 (2019) - 2018
- [i2]Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru:
Model Cards for Model Reporting. CoRR abs/1810.03993 (2018) - [i1]Ben Hutchinson, Margaret Mitchell:
50 Years of Test (Un)fairness: Lessons for Machine Learning. CoRR abs/1811.10104 (2018)
2000 – 2009
- 2009
- [c8]Casey Whitelaw, Ben Hutchinson, Grace Chung, Ged Ellis:
Using the Web for Language Independent Spellchecking and Autocorrection. EMNLP 2009: 890-899 - 2007
- [c7]Dominique Estival, Tanja Gaustad, Son Bao Pham, Will Radford, Ben Hutchinson:
TAT: An Author Profiling Tool with Application to Arabic Emails. ALTA 2007: 21-30 - 2005
- [b1]Ben Hutchinson:
The automatic acquisition of knowledge about discourse connectives. University of Edinburgh, UK, 2005 - [c6]Ben Hutchinson:
Modelling the Substitutability of Discourse Connectives. ACL 2005: 149-156 - [c5]Ben Hutchinson:
MDL-based Acquisition of Substitutability Relationships between Discourse Connectives. IJCAI 2005: 1690-1691 - 2004
- [c4]Ben Hutchinson:
Acquiring the Meaning of Discourse Markers. ACL 2004: 684-691 - [c3]Ben Hutchinson:
Mining the Web for Discourse Markers. LREC 2004 - 2001
- [c2]Ben Hutchinson, Cécile Pereira:
Um, one large pizza. A preliminary study of disfluency modelling for improving ASR. DiSS 2001: 77-80 - [c1]Ben Hutchinson:
A functional approach to speech recognition evaluation. INTERSPEECH 2001: 1683-1686
Coauthor Index
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last updated on 2024-10-10 22:16 CEST by the dblp team
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