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ORCIDSayash Kapoor
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2020 – today
- 2025
[i19]Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Philip Fox, Ben Garfinkel, Danielle Goldfarb, Hoda Heidari, Anson Ho, Sayash Kapoor, Leila Khalatbari, Shayne Longpre, Sam Manning, Vasilios Mavroudis, Mantas Mazeika, Julian Michael, Jessica Newman, Kwan Yee Ng, Chinasa T. Okolo, Deborah Raji, Girish Sastry, Elizabeth Seger, Theodora Skeadas, Tobin South, Emma Strubell, Florian Tramèr, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Olubayo Adekanmbi, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Fredrik Heintz, Geoffrey Hinton, Nick R. Jennings, Andreas Krause, Susan Leavy, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Fahad Albalawi, Marwan Alserkal, Olubunmi Ajala, Guillaume Avrin, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Bronwyn Fox, Amandeep Singh Gill, Ahmet Halit Hatip, Juha Heikkilä, Gill Jolly, Ziv Katzir, Hiroaki Kitano, Antonio Krüger, Chris Johnson, Saif M. Khan, Kyoung Mu Lee, Dominic Vincent Ligot, Oleksii Molchanovskyi, Andrea Monti, Nusu Mwamanzi, Mona Nemer, Nuria Oliver, José Ramón López Portillo, Balaraman Ravindran, Raquel Pezoa Rivera, Hammam Riza, Crystal Rugege, Ciarán Seoighe, Jerry Sheehan, Haroon Sheikh, Denise Wong, Yi Zeng:
International AI Safety Report. CoRR abs/2501.17805 (2025)- 2024
- [c7]Rishi Bommasani, Kevin Klyman, Shayne Longpre, Betty Xiong, Sayash Kapoor, Nestor Maslej, Arvind Narayanan, Percy Liang:
Foundation Model Transparency Reports. AIES (1) 2024: 181-195 - [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 - [i18]Sayash Kapoor, Peter Henderson, Arvind Narayanan:
Promises and pitfalls of artificial intelligence for legal applications. CoRR abs/2402.01656 (2024) - [i17]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) - [i16]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) - [i15]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) - [i14]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) - [i13]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) - [i12]Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, Nitya Nadgir, Arvind Narayanan:
AI Agents That Matter. CoRR abs/2407.01502 (2024) - [i11]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) - [i10]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) - [i9]Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan:
Inference Scaling fLaws: The Limits of LLM Resampling with Imperfect Verifiers. CoRR abs/2411.17501 (2024) - [i8]Aidan Peppin, Anka Reuel, Stephen Casper, Elliot Jones, Andrew Strait, Usman Anwar, Anurag Agrawal, Sayash Kapoor, Sanmi Koyejo, Marie Pellat, Rishi Bommasani, Nick Frosst, Sara Hooker:
The Reality of AI and Biorisk. CoRR abs/2412.01946 (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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