Kathleen Creel

11 papers A* 2B 1Journal 4Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Allocation Multiplicity: Evaluating the Promises of the Rashomon Set. FAccT Shomik Jain, Margaret Wang, Kathleen Creel, Ashia Wilson
2025	J	`jnl`	Allocation Multiplicity: Evaluating the Promises of the Rashomon Set. CoRR Shomik Jain, Margaret Wang, Kathleen Creel, Ashia Wilson
2025	J	`jnl`	Homogeneous Algorithms Can Reduce Competition in Personalized Pricing. CoRR Nathanael Jo, Kathleen Creel, Ashia Wilson, Manish Raghavan
2024	—	`conf`	Algorithmic Pluralism: A Structural Approach To Equal Opportunity. FAccT Shomik Jain, Vinith M. Suriyakumar, Kathleen Creel, Ashia Wilson
2024	A*	`conf`	Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized. ICML Shomik Jain, Kathleen Creel, Ashia Camage Wilson
2024	J	`jnl`	Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized. CoRR Shomik Jain, Kathleen Creel, Ashia Wilson
2023	A*	`conf`	Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes. NeurIPS Connor Toups, Rishi Bommasani, Kathleen Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang
2022	—	`conf`	Nifty Assignments. SIGCSE (2) Nick Parlante, Julie Zelenski, Eric S. Roberts, Jed Rembold, Ben Stephenson, Jonathan Hudson, Stephanie Valentine, Juliette Woodrow, Kathleen Creel, Nick Bowman, Larry Joshua Crotts, Andrew Matzureff, Mike Izbicki
2021	J	`jnl`	On the Opportunities and Risks of Foundation Models. CoRR Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.
2021	—	`conf`	The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision Making Systems. FAccT Kathleen Creel, Deborah Hellman
2019	B	`conf`	What makes a good explanation? Cognitive dimensions of explaining intelligent machines. CogSci Roberto Confalonieri, Tarek R. Besold, Tillman Weyde, Kathleen Creel, Tania Lombrozo, Shane T. Mueller, Patrick Shafto