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ORCIDSayash Kapoor
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2020 – today
- 2024
[c6]Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan:
Position: On the Societal Impact of Open Foundation Models. ICML 2024- [c5]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
Position: A Safe Harbor for AI Evaluation and Red Teaming. ICML 2024 - [i16]Sayash Kapoor, Peter Henderson, Arvind Narayanan:
Promises and pitfalls of artificial intelligence for legal applications. CoRR abs/2402.01656 (2024) - [i15]Rishi Bommasani, Kevin Klyman, Shayne Longpre, Betty Xiong, Sayash Kapoor, Nestor Maslej, Arvind Narayanan, Percy Liang:
Foundation Model Transparency Reports. CoRR abs/2402.16268 (2024) - [i14]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
A Safe Harbor for AI Evaluation and Red Teaming. CoRR abs/2403.04893 (2024) - [i13]Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan:
On the Societal Impact of Open Foundation Models. CoRR abs/2403.07918 (2024) - [i12]Adrien Basdevant, Camille François, Victor Storchan, Kevin Bankston, Ayah Bdeir, Brian Behlendorf, Mérouane Debbah, Sayash Kapoor, Yann LeCun, Mark Surman, Helen King-Turvey, Nathan Lambert, Stefano Maffulli, Nik Marda, Govind Shivkumar, Justine Tunney:
Towards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence. CoRR abs/2405.15802 (2024) - [i11]Shayne Longpre, Stella Biderman, Alon Albalak, Hailey Schoelkopf, Daniel McDuff, Sayash Kapoor, Kevin Klyman, Kyle Lo, Gabriel Ilharco, Nay San, Maribeth Rauh, Aviya Skowron, Bertie Vidgen, Laura Weidinger, Arvind Narayanan, Victor Sanh, David Ifeoluwa Adelani, Percy Liang, Rishi Bommasani, Peter Henderson, Sasha Luccioni, Yacine Jernite, Luca Soldaini:
The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources. CoRR abs/2406.16746 (2024) - [i10]Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, Nitya Nadgir, Arvind Narayanan:
AI Agents That Matter. CoRR abs/2407.01502 (2024) - [i9]Rishi Bommasani, Kevin Klyman, Sayash Kapoor, Shayne Longpre, Betty Xiong, Nestor Maslej, Percy Liang:
The Foundation Model Transparency Index v1.1: May 2024. CoRR abs/2407.12929 (2024) - [i8]Zachary S. Siegel, Sayash Kapoor, Nitya Nagdir, Benedikt Stroebl, Arvind Narayanan:
CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark. CoRR abs/2409.11363 (2024) - 2023
- [j5]Sayash Kapoor
, Arvind Narayanan:
Leakage and the reproducibility crisis in machine-learning-based science. Patterns 4(9): 100804 (2023) - [c4]Angelina Wang, Sayash Kapoor, Solon Barocas, Arvind Narayanan:
Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy. FAccT 2023: 626 - [i7]Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan:
REFORMS: Reporting Standards for Machine Learning Based Science. CoRR abs/2308.07832 (2023) - [i6]Rishi Bommasani, Kevin Klyman, Shayne Longpre, Sayash Kapoor, Nestor Maslej, Betty Xiong, Daniel Zhang, Percy Liang:
The Foundation Model Transparency Index. CoRR abs/2310.12941 (2023) - 2022
- [j4]Sayash Kapoor, Matthew Sun, Mona Wang, Klaudia Jazwinska, Elizabeth Anne Watkins:
Weaving Privacy and Power: On the Privacy Practices of Labor Organizers in the U.S. Technology Industry. Proc. ACM Hum. Comput. Interact. 6(CSCW2): 1-33 (2022) - [c3]Jessica Hullman, Sayash Kapoor, Priyanka Nanayakkara, Andrew Gelman, Arvind Narayanan:
The Worst of Both Worlds: A Comparative Analysis of Errors in Learning from Data in Psychology and Machine Learning. AIES 2022: 335-348 - [i5]Jessica Hullman, Sayash Kapoor, Priyanka Nanayakkara, Andrew Gelman, Arvind Narayanan:
The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning. CoRR abs/2203.06498 (2022) - [i4]Sayash Kapoor, Matthew Sun, Mona Wang, Klaudia Jazwinska, Elizabeth Anne Watkins:
Weaving Privacy and Power: On the Privacy Practices of Labor Organizers in the U.S. Technology Industry. CoRR abs/2206.00035 (2022) - [i3]Sayash Kapoor, Arvind Narayanan:
Leakage and the Reproducibility Crisis in ML-based Science. CoRR abs/2207.07048 (2022) - 2021
- [j3]Mac Andre Arboleda, Palak Dudani, Sayash Kapoor, Lorna Xu:
The platform as the city. Interactions 28(6): 12-15 (2021)
2010 – 2019
- 2019
- [j2]L. Elisa Celis, Sayash Kapoor, Farnood Salehi, Vijay Keswani, Nisheeth K. Vishnoi:
A dashboard for controlling polarization in personalization. AI Commun. 32(1): 77-89 (2019) - [j1]Sayash Kapoor, Kumar Kshitij Patel, Purushottam Kar:
Corruption-tolerant bandit learning. Mach. Learn. 108(4): 687-715 (2019) - [c2]L. Elisa Celis, Sayash Kapoor, Farnood Salehi, Nisheeth K. Vishnoi:
Controlling Polarization in Personalization: An Algorithmic Framework. FAT 2019: 160-169 - 2018
- [c1]Sayash Kapoor, Vijay Keswani, Nisheeth K. Vishnoi, L. Elisa Celis:
Balanced News Using Constrained Bandit-based Personalization. IJCAI 2018: 5835-5837 - [i2]L. Elisa Celis, Sayash Kapoor, Farnood Salehi, Nisheeth K. Vishnoi:
An Algorithmic Framework to Control Bias in Bandit-based Personalization. CoRR abs/1802.08674 (2018) - [i1]Sayash Kapoor, Vijay Keswani, Nisheeth K. Vishnoi, L. Elisa Celis:
Balanced News Using Constrained Bandit-based Personalization. CoRR abs/1806.09202 (2018)
Coauthor Index
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