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William Agnew
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2020 – today
- 2024
- [j2]William Agnew:
What Can AI Ethics Learn from Anarchism? XRDS 30(4) (2024) - [c10]William Agnew
, A. Stevie Bergman
The Illusion of Artificial Inclusion. CHI 2024: 286:1-286:12 - [c9]Rachel Hong
Who's in and who's out? A case study of multimodal CLIP-filtering in DataComp. EAAMO 2024: 4:1-4:17 - [i15]William Agnew, A. Stevie Bergman, Jennifer Chien, Mark Díaz, Seliem El-Sayed, Jaylen Pittman
The illusion of artificial inclusion. CoRR abs/2401.08572 (2024) - [i14]Rachel Hong, William Agnew, Tadayoshi Kohno, Jamie Morgenstern:
Who's in and who's out? A case study of multimodal CLIP-filtering in DataComp. CoRR abs/2405.08209 (2024) - [i13]Shivani Kapania, William Agnew, Motahhare Eslami, Hoda Heidari, Sarah E. Fox:
'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participants. CoRR abs/2409.19430 (2024) - [i12]William Agnew, Julia Barnett, Annie Chu, Rachel Hong, Michael Feffer, Robin Netzorg, Harry H. Jiang, Ezra Awumey, Sauvik Das:
Sound Check: Auditing Audio Datasets. CoRR abs/2410.13114 (2024) - [i11]William Agnew, Harry H. Jiang, Cella Sum, Maarten Sap, Sauvik Das:
Data Defenses Against Large Language Models. CoRR abs/2410.13138 (2024) - 2023
- [c8]Nathan Dennler
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms. AIES 2023: 375-386 - [c7]A. Stevie Bergman
Representation in AI Evaluations. FAccT 2023: 519-533 - [c6]Organizers Of QueerInAI
Queer In AI: A Case Study in Community-Led Participatory AI. FAccT 2023: 1882-1895 - [i10]Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli
Queer In AI: A Case Study in Community-Led Participatory AI. CoRR abs/2303.16972 (2023) - [i9]Irene Solaiman, Zeerak Talat
Evaluating the Social Impact of Generative AI Systems in Systems and Society. CoRR abs/2306.05949 (2023) - [i8]Organizers Of QueerInAI, Nathaniel Dennler, Anaelia Ovalle, Ashwin Singh, Luca Soldaini, Arjun Subramonian, Huy Tu, William Agnew, Avijit Ghosh, Kyra Yee, Irene Font Peradejordi, Zeerak Talat, Mayra Russo, Jess de Jesus de Pinho Pinhal:
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms. CoRR abs/2307.10223 (2023) - [i7]Pratyusha Ria Kalluri, William Agnew, Myra Cheng, Kentrell Owens, Luca Soldaini, Abeba Birhane:
The Surveillance AI Pipeline. CoRR abs/2309.15084 (2023) - 2022
- [j1]Hetvi Jethwani, Arjun Subramonian, William Agnew, MaryLena Bleile, Sarthak Arora, Maria Ryskina, Jeffrey Xiong:
Queer in AI. XRDS 28(4): 18-21 (2022) - [c5]Abeba Birhane, Pratyusha Kalluri, Dallas Card
The Values Encoded in Machine Learning Research. FAccT 2022: 173-184 - [c4]Andrew Hundt, William Agnew, Vicky Zeng, Severin Kacianka, Matthew C. Gombolay:
Robots Enact Malignant Stereotypes. FAccT 2022: 743-756 - [i6]Andrew Hundt, William Agnew, Vicky Zeng, Severin Kacianka, Matthew C. Gombolay:
Robots Enact Malignant Stereotypes. CoRR abs/2207.11569 (2022) - 2021
- [c3]Jesse Dodge, Maarten Sap, Ana Marasovic, William Agnew, Gabriel Ilharco, Dirk Groeneveld
Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus. EMNLP (1) 2021: 1286-1305 - [i5]Jesse Dodge, Maarten Sap, Ana Marasovic, William Agnew, Gabriel Ilharco, Dirk Groeneveld, Matt Gardner:
Documenting the English Colossal Clean Crawled Corpus. CoRR abs/2104.08758 (2021) - [i4]Abeba Birhane, Pratyusha Kalluri, Dallas Card, William Agnew, Ravit Dotan, Michelle Bao:
The Values Encoded in Machine Learning Research. CoRR abs/2106.15590 (2021) - 2020
- [c2]William Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Yubo Wang, Pedro Domingos, Siddhartha S. Srinivasa:
Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity. CoRL 2020: 1498-1508 - [i3]William Agnew, Pedro Domingos:
Self-Supervised Object-Level Deep Reinforcement Learning. CoRR abs/2003.01384 (2020) - [i2]William Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Caelen Wang, Pedro Domingos, Siddhartha S. Srinivasa:
Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity. CoRR abs/2009.13146 (2020)
2010 – 2019
- 2016
- [c1]William Agnew, Michael Fischer, Ian T. Foster, Kyle Chard:
An Ensemble-Based Recommendation Engine for Scientific Data Transfers. DataCloud@SC 2016: 9-16 - [i1]William Agnew, Hyunjong Lee, Minsung Jang, Ada Gavrilovska, Karsten Schwan:
Drawing Insights from "Big Data" Machine Learning Literature using Textual Features Why are some novels considered to be literature? A. predictive model of literary judgments shows that textual features are important. Andreas van Cranenburgh: Reducing Mobile Throttling from Temperature by Offloading Apps. Tiny Trans. Comput. Sci. 4 (2016)
Coauthor Index
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last updated on 2024-11-25 22:44 CET by the dblp team
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