Sendhil Mullainathan

49 papers A* 17A 2Journal 28Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AI Behavioral Science. CoRR Matthew O. Jackson, Qiaozhu Mei, Stephanie W. Wang, Yutong Xie, Walter Yuan, Seth Benzell, Erik Brynjolfsson, Colin F. Camerer, James Evans, Brian Jabarian, Jon M. Kleinberg, Juanjuan Meng, Sendhil Mullainathan, Asuman Ozdaglar, Thomas Pfeiffer, Moshe Tennenholtz, Robb Willer, Diyi Yang, Teng Ye
2025	A*	`conf`	Potemkin Understanding in Large Language Models. ICML Marina Mancoridis, Bec Weeks, Keyon Vafa, Sendhil Mullainathan
2025	J	`jnl`	Potemkin Understanding in Large Language Models. CoRR Marina Mancoridis, Bec Weeks, Keyon Vafa, Sendhil Mullainathan
2025	A*	`conf`	What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models. ICML Keyon Vafa, Peter G. Chang, Ashesh Rambachan, Sendhil Mullainathan
2025	J	`jnl`	What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models. CoRR Keyon Vafa, Peter G. Chang, Ashesh Rambachan, Sendhil Mullainathan
2025	J	`jnl`	What's Producible May Not Be Reachable: Measuring the Steerability of Generative Models. CoRR Keyon Vafa, Sarah Bentley, Jon M. Kleinberg, Sendhil Mullainathan
2024	A*	`conf`	Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function. ICML Keyon Vafa, Ashesh Rambachan, Sendhil Mullainathan
2024	J	`jnl`	Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function. CoRR Keyon Vafa, Ashesh Rambachan, Sendhil Mullainathan
2024	A*	`conf`	Evaluating the World Model Implicit in a Generative Model. NeurIPS Keyon Vafa, Justin Y. Chen, Ashesh Rambachan, Jon M. Kleinberg, Sendhil Mullainathan
2024	J	`jnl`	Evaluating the World Model Implicit in a Generative Model. CoRR Keyon Vafa, Justin Y. Chen, Jon M. Kleinberg, Sendhil Mullainathan, Ashesh Rambachan
2024	A*	`conf`	Language Generation in the Limit. NeurIPS Jon M. Kleinberg, Sendhil Mullainathan
2024	J	`jnl`	Language Generation in the Limit. CoRR Jon M. Kleinberg, Sendhil Mullainathan
2024	J	`jnl`	Large Language Models: An Applied Econometric Framework. CoRR Jens Ludwig, Sendhil Mullainathan, Ashesh Rambachan
2023	J	`jnl`	Use large language models to promote equity. CoRR Emma Pierson, Divya Shanmugam, Rajiv Movva, Jon M. Kleinberg, Monica Agrawal, Mark Dredze, Kadija Ferryman, Judy Wawira Gichoya, Dan Jurafsky, Pang Wei Koh, Karen Levy, Sendhil Mullainathan, Ziad Obermeyer, Harini Suresh, Keyon Vafa
2022	A*	`conf`	The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization. EC Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
2022	J	`jnl`	The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization. CoRR Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
2021	A*	`conf`	Simplicity creates inequity: implications for fairness, stereotypes, and interpretability (invited paper). STOC Jon M. Kleinberg, Sendhil Mullainathan
2020	J	`jnl`	Algorithms as discrimination detectors. Proc. Natl. Acad. Sci. USA Jon M. Kleinberg, Jens Ludwig, Sendhil Mullainathan, Cass R. Sunstein
2020	—	`conf`	Characterizing the Value of Information in Medical Notes. EMNLP (Findings) Chao-Chun Hsu, Shantanu Karnwal, Sendhil Mullainathan, Ziad Obermeyer, Chenhao Tan
2020	J	`jnl`	Characterizing the Value of Information in Medical Notes. CoRR Chao-Chun Hsu, Shantanu Karnwal, Sendhil Mullainathan, Ziad Obermeyer, Chenhao Tan
2020	J	`jnl`	Quantifying the Causal Effects of Conversational Tendencies. CoRR Justine Zhang, Sendhil Mullainathan, Cristian Danescu-Niculescu-Mizil
2020	J	`jnl`	Quantifying the Causal Effects of Conversational Tendencies. Proc. ACM Hum. Comput. Interact. Justine Zhang, Sendhil Mullainathan, Cristian Danescu-Niculescu-Mizil
2020	J	`jnl`	The Data Station: Combining Data, Compute, and Market Forces. CoRR Raul Castro Fernandez, Kyle Chard, Ben Blaiszik, Sanjay Krishnan, Aaron J. Elmore, Ziad Obermeyer, Josh Risley, Sendhil Mullainathan, Michael J. Franklin, Ian T. Foster
2019	A*	`conf`	Direct Uncertainty Prediction for Medical Second Opinions. ICML Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Robert D. Kleinberg, Sendhil Mullainathan, Jon M. Kleinberg
2019	J	`jnl`	Discrimination in the Age of Algorithms. CoRR Jon M. Kleinberg, Jens Ludwig, Sendhil Mullainathan, Cass R. Sunstein
2019	A*	`conf`	Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography. ICML Andrew C. Miller, Ziad Obermeyer, John P. Cunningham, Sendhil Mullainathan
2019	—	`conf`	Dissecting Racial Bias in an Algorithm that Guides Health Decisions for 70 Million People. FAT Ziad Obermeyer, Sendhil Mullainathan
2019	J	`jnl`	Measuring the Completeness of Theories. CoRR Drew Fudenberg, Jon M. Kleinberg, Annie Liang, Sendhil Mullainathan
2019	A*	`conf`	Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability. EC Jon M. Kleinberg, Sendhil Mullainathan
2019	J	`jnl`	The Algorithmic Automation Problem: Prediction, Triage, and Human Effort. CoRR Maithra Raghu, Katy Blumer, Greg Corrado, Jon M. Kleinberg, Ziad Obermeyer, Sendhil Mullainathan
2018	J	`jnl`	A Probabilistic Model of Cardiac Physiology and Electrocardiograms. CoRR Andrew C. Miller, Ziad Obermeyer, David M. Blei, John P. Cunningham, Sendhil Mullainathan
2018	A*	`conf`	Algorithmic Fairness and the Social Welfare Function. EC Sendhil Mullainathan
2018	J	`jnl`	Direct Uncertainty Prediction with Applications to Healthcare. CoRR Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Sendhil Mullainathan, Jon M. Kleinberg
2018	J	`jnl`	Measuring the Stability of EHR- and EKG-based Predictive Models. CoRR Andrew C. Miller, Ziad Obermeyer, Sendhil Mullainathan
2018	J	`jnl`	Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability. CoRR Jon M. Kleinberg, Sendhil Mullainathan
2017	J	`jnl`	Assessing Human Error Against a Benchmark of Perfection. ACM Trans. Knowl. Discov. Data Ashton Anderson, Jon M. Kleinberg, Sendhil Mullainathan
2017	J	`jnl`	Comparison-Based Choices. CoRR Jon M. Kleinberg, Sendhil Mullainathan, Johan Ugander
2017	A*	`conf`	Comparison-based Choices. EC Jon M. Kleinberg, Sendhil Mullainathan, Johan Ugander
2017	A	`conf`	Inherent Trade-Offs in the Fair Determination of Risk Scores. ITCS Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
2017	A*	`conf`	The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables. KDD Himabindu Lakkaraju, Jon M. Kleinberg, Jure Leskovec, Jens Ludwig, Sendhil Mullainathan
2017	J	`jnl`	The Theory is Predictive, but is it Complete? An Application to Human Perception of Randomness. CoRR Jon M. Kleinberg, Annie Liang, Sendhil Mullainathan
2017	A*	`conf`	The Theory is Predictive, but is it Complete?: An Application to Human Perception of Randomness. EC Jon M. Kleinberg, Annie Liang, Sendhil Mullainathan
2016	A*	`conf`	Assessing Human Error Against a Benchmark of Perfection. KDD Ashton Anderson, Jon M. Kleinberg, Sendhil Mullainathan
2016	J	`jnl`	Assessing Human Error Against a Benchmark of Perfection. CoRR Ashton Anderson, Jon M. Kleinberg, Sendhil Mullainathan
2016	J	`jnl`	Getting to the Top of Mind: How Reminders Increase Saving. Manag. Sci. Dean S. Karlan, Margaret McConnell, Sendhil Mullainathan, Jonathan Zinman
2016	J	`jnl`	Inherent Trade-Offs in the Fair Determination of Risk Scores. CoRR Jon M. Kleinberg, Sendhil Mullainathan, Manish Raghavan
2015	A	`conf`	A Bayesian Framework for Modeling Human Evaluations. SDM Himabindu Lakkaraju, Jure Leskovec, Jon M. Kleinberg, Sendhil Mullainathan
2014	A*	`conf`	Bugbears or legitimate threats?: (social) scientists' criticisms of machine learning? KDD Sendhil Mullainathan
1993	A*	`conf`	Resource Bounds and Combinations of Consensus Objects. PODC Jon M. Kleinberg, Sendhil Mullainathan