Documenting large webtext corpora: A case study on the colossal clean crawled corpus J Dodge, M Sap, A Marasović, W Agnew, G Ilharco, D Groeneveld, ... arXiv preprint arXiv:2104.08758, 2021 | 290 | 2021 |
The values encoded in machine learning research A Birhane, P Kalluri, D Card, W Agnew, R Dotan, M Bao 2022 ACM Conference on Fairness, Accountability, and Transparency, 173-184, 2022 | 243 | 2022 |
Evaluating the Social Impact of Generative AI Systems in Systems and Society I Solaiman, Z Talat, W Agnew, L Ahmad, D Baker, SL Blodgett, ... arXiv preprint arXiv:2306.05949, 2023 | 41 | 2023 |
Robots Enact Malignant Stereotypes A Hundt, W Agnew, V Zeng, S Kacianka, M Gombolay 2022 ACM Conference on Fairness, Accountability, and Transparency, 743-756, 2022 | 34 | 2022 |
Amodal 3d reconstruction for robotic manipulation via stability and connectivity W Agnew, C Xie, A Walsman, O Murad, Y Wang, P Domingos, S Srinivasa Conference on Robot Learning, 1498-1508, 2021 | 21 | 2021 |
Queer In AI: A Case Study in Community-Led Participatory AI OO Queerinai, A Ovalle, A Subramonian, A Singh, C Voelcker, ... Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 11 | 2023 |
Representation in AI Evaluations AS Bergman, LA Hendricks, M Rauh, B Wu, W Agnew, M Kunesch, I Duan, ... Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 9 | 2023 |
The Surveillance AI Pipeline PR Kalluri, W Agnew, M Cheng, K Owens, L Soldaini, A Birhane arXiv preprint arXiv:2309.15084, 2023 | 4 | 2023 |
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms N Dennler, A Ovalle, A Singh, L Soldaini, A Subramonian, H Tu, W Agnew, ... arXiv preprint arXiv:2307.10223, 2023 | 3 | 2023 |
Unsupervised Object-Level Deep Reinforcement Learning W Agnew, P Domingos NeurIPS Workshop on Deep RL, 2018 | 3 | 2018 |
An ensemble-based recommendation engine for scientific data transfers W Agnew, M Fischer, I Foster, K Chard 2016 Seventh International Workshop on Data-Intensive Computing in the …, 2016 | 3 | 2016 |
Queer in AI H Jethwani, A Subramonian, W Agnew, ML Bleile, S Arora, M Ryskina, ... XRDS: Crossroads, The ACM Magazine for Students 28 (4), 18-21, 2022 | 2 | 2022 |
Relevance-Guided Modeling of Object Dynamics for Reinforcement Learning W Agnew, P Domingos arXiv preprint arXiv:2003.01384, 2020 | 2* | 2020 |
The illusion of artificial inclusion W Agnew, AS Bergman, J Chien, M Díaz, S El-Sayed, J Pittman, ... arXiv preprint arXiv:2401.08572, 2024 | 1 | 2024 |
Queer In AI: A Case Study in Community-Led Participatory AI A Ovalle, A Subramonian, A Singh, C Voelcker, DJ Sutherland, D Locatelli, ... arXiv preprint arXiv:2303.16972, 2023 | | 2023 |
Documenting the English Colossal Clean Crawled Corpus J Dodge, M Sap, A Marasovic, W Agnew, G Ilharco, D Groeneveld, ... arXiv preprint arXiv:2104.08758, 2021 | | 2021 |
Touring Dataland? Automated Recommendations for the Big Data Traveler W Agnew, K Chard, I Foster, M Fischer | | 2016 |
Technologies of Resistance to AI W Agnew, KR McKee, J Kay | | |
Crossroads The ACM Magazine for Students H Jethwani, A Subramonian, W Agnew, ML Bleile, S Arora, M Ryskina, ... | | |
TeSLA: Thermal Service Level Agreement for Mobile Devices HJ Lee, M Jang, W Agnew, K Schwan, A Gavrilovska | | |