Adam Tauman Kalai

109 papers A* 29A 4B 5C 2Misc 1Journal 57Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Consensus Sampling for Safer Generative AI. CoRR Adam Tauman Kalai, Yael Tauman Kalai, Or Zamir
2025	A*	`conf`	First-Person Fairness in Chatbots. ICLR Tyna Eloundou, Alex Beutel, David G. Robinson, Keren Gu, Anna-Luisa Brakman, Pamela Mishkin, Meghan Shah, Johannes Heidecke, Lilian Weng, Adam Tauman Kalai
2025	J	`jnl`	On Non-interactive Evaluation of Animal Communication Translators. CoRR Orr Paradise, David F. Gruber, Adam Tauman Kalai
2025	J	`jnl`	The Singapore Consensus on Global AI Safety Research Priorities. CoRR Yoshua Bengio, Tegan Maharaj, Luke Ong, Stuart Russell, Dawn Song, Max Tegmark, Lan Xue, Ya-Qin Zhang, Stephen Casper, Wan Sie Lee, Sören Mindermann, Vanessa Wilfred, Vidhisha Balachandran, Fazl Barez, Michael Belinsky, Imane Bello, Malo Bourgon, Mark Brakel, Siméon Campos, Duncan Cass-Beggs, Jiahao Chen, Rumman Chowdhury, Kuan Chua Seah, Jeff Clune, Juntao Dai, Agnès Delaborde, Nouha Dziri, Francisco Eiras, Joshua Engels, Jinyu Fan, Adam Gleave, Noah Goodman, Fynn Heide, Johannes Heidecke, Dan Hendrycks, Cyrus Hodes, Bryan Low Kian Hsiang, Minlie Huang, Sami Jawhar, Wang Jingyu, Adam Tauman Kalai, Meindert Kamphuis, Mohan S. Kankanhalli, Subhash Kantamneni, Mathias Bonde Kirk, Thomas Kwa, Jeffrey Ladish, Kwok-Yan Lam, Wan Lee Sie, Taewhi Lee, Xiaojian Li, Jiajun Liu, Chaochao Lu, Yifan Mai, Richard Mallah, Julian Michael, Nick Moës, Simon Möller, Kihyuk Nam, Kwan Yee Ng, Mark Nitzberg, Besmira Nushi, Seán Ó hÉigeartaigh, Alejandro Ortega, Pierre Peigné, James Petrie, Benjamin Prud'homme, Reihaneh Rabbany, Nayat Sánchez-Pi, Sarah Schwettmann, Buck Shlegeris, Saad Siddiqui, Aradhana Sinha, Martín Soto, Cheston Tan, Dong Ting, William-Chandra Tjhi, Robert Trager, Brian Tse, Anthony Tung K. H., John Willes, Denise Wong, Wei Xu, Rongwu Xu, Yi Zeng, HongJiang Zhang, Djordje Zikelic
2025	J	`jnl`	Why Language Models Hallucinate. CoRR Adam Tauman Kalai, Ofir Nachum, Santosh S. Vempala, Edwin Zhang
2024	J	`jnl`	Beyond dominance and Nash: Ranking equilibria by critical mass. Games Econ. Behav. Adam Tauman Kalai, Ehud Kalai
2024	A*	`conf`	Calibrated Language Models Must Hallucinate. STOC Adam Tauman Kalai, Santosh S. Vempala
2024	J	`jnl`	First-Person Fairness in Chatbots. CoRR Tyna Eloundou, Alex Beutel, David G. Robinson, Keren Gu-Lemberg, Anna-Luisa Brakman, Pamela Mishkin, Meghan Shah, Johannes Heidecke, Lilian Weng, Adam Tauman Kalai
2024	A	`conf`	Loss Minimization Yields Multicalibration for Large Neural Networks. ITCS Jaroslaw Blasiok, Parikshit Gopalan, Lunjia Hu, Adam Tauman Kalai, Preetum Nakkiran
2024	J	`jnl`	Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding. CoRR Mirac Suzgun, Adam Tauman Kalai
2023	A*	`conf`	A Theory of Unsupervised Translation Motivated by Understanding Animal Communication. NeurIPS Shafi Goldwasser, David F. Gruber, Adam Tauman Kalai, Orr Paradise
2023	J	`jnl`	Calibrated Language Models Must Hallucinate. CoRR Adam Tauman Kalai, Santosh S. Vempala
2023	—	`conf`	Comparing Different Approaches to Generating Mathematics Explanations Using Large Language Models. AIED (Posters/Late Breaking Results/...) Ethan Prihar, Morgan P. Lee, Mia Hopman, Adam Tauman Kalai, Sofia Vempala, Allison Wang, Gabriel Wickline, Aly Murray, Neil T. Heffernan
2023	J	`jnl`	Do Language Models Know When They're Hallucinating References? CoRR Ayush Agrawal, Lester Mackey, Adam Tauman Kalai
2023	A*	`conf`	Language Models Can Teach Themselves to Program Better. ICLR Patrick Haluptzok, Matthew Bowers, Adam Tauman Kalai
2023	J	`jnl`	Loss minimization yields multicalibration for large neural networks. CoRR Jaroslaw Blasiok, Parikshit Gopalan, Lunjia Hu, Adam Tauman Kalai, Preetum Nakkiran
2023	A*	`conf`	Partial Matrix Completion. NeurIPS Elad Hazan, Adam Tauman Kalai, Varun Kanade, Clara Mohri, Y. Jennifer Sun
2023	J	`jnl`	Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation. CoRR Eric Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai
2023	J	`jnl`	Social norm bias: residual harms of fairness-aware algorithms. Data Min. Knowl. Discov. Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai
2023	J	`jnl`	Testing Language Model Agents Safely in the Wild. CoRR Silen Naihin, David Atkinson, Marc Green, Merwane Hamadi, Craig Swift, Douglas Schonholtz, Adam Tauman Kalai, David Bau
2023	J	`jnl`	Textbooks Are All You Need. CoRR Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, Sébastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, Yuanzhi Li
2023	A*	`conf`	Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies. ICML Gati V. Aher, Rosa I. Arriaga, Adam Tauman Kalai
2022	J	`jnl`	A Theory of Unsupervised Translation Motivated by Understanding Animal Communication. CoRR Shafi Goldwasser, David F. Gruber, Adam Tauman Kalai, Orr Paradise
2022	J	`jnl`	Language Models Can Teach Themselves to Program Better. CoRR Patrick Haluptzok, Matthew Bowers, Adam Tauman Kalai
2022	A	`conf`	Omnipredictors. ITCS Parikshit Gopalan, Adam Tauman Kalai, Omer Reingold, Vatsal Sharan, Udi Wieder
2022	J	`jnl`	Partial Matrix Completion. CoRR Varun Kanade, Elad Hazan, Adam Tauman Kalai
2022	J	`jnl`	Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. CoRR Surbhi Goel, Sham M. Kakade, Adam Tauman Kalai, Cyril Zhang
2022	J	`jnl`	Using Large Language Models to Simulate Multiple Humans. CoRR Gati Aher, Rosa I. Arriaga, Adam Tauman Kalai
2022	J	`jnl`	Why GANs are overkill for NLP. CoRR David Alvarez-Melis, Vikas Garg, Adam Tauman Kalai
2021	B	`conf`	Efficient Learning with Arbitrary Covariate Shift. ALT Adam Tauman Kalai, Varun Kanade
2021	A	`conf`	Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization. AISTATS Vikas K. Garg, Adam Tauman Kalai, Katrina Ligett, Zhiwei Steven Wu
2021	J	`jnl`	Omnipredictors. CoRR Parikshit Gopalan, Adam Tauman Kalai, Omer Reingold, Vatsal Sharan, Udi Wieder
2021	J	`jnl`	Programming Puzzles. CoRR Tal Schuster, Ashwin Kalyan, Oleksandr Polozov, Adam Tauman Kalai
2021	J	`jnl`	Social Norm Bias: Residual Harms of Fairness-Aware Algorithms. CoRR Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai
2021	J	`jnl`	Towards optimally abstaining from prediction. CoRR Adam Tauman Kalai, Varun Kanade
2020	A*	`conf`	Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples. NeurIPS Shafi Goldwasser, Adam Tauman Kalai, Yael Kalai, Omar Montasser
2020	J	`jnl`	Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples. CoRR Shafi Goldwasser, Adam Tauman Kalai, Yael Tauman Kalai, Omar Montasser
2020	—	`conf`	HAI-GEN 2020 : Workshop on Human-AI Co-Creation with Generative Models. HAI-GEN+user2agent@IUI Werner Geyer, Lydia B. Chilton, Ranjitha Kumar, Adam Tauman Kalai
2020	—	`conf`	HAI-GEN 2020: Workshop on Human-AI Co-Creation with Generative Models. IUI Companion Werner Geyer, Lydia B. Chilton, Ranjitha Kumar, Adam Tauman Kalai
2020	Misc	`conf`	Identifying unpredictable test examples with worst-case guarantees. ITA Shafi Goldwasser, Adam Tauman Kalai, Yael Tauman Kalai, Omar Montasser
2020	—	`conf`	The disparate equilibria of algorithmic decision making when individuals invest rationally. FAT* Lydia T. Liu, Ashia Wilson, Nika Haghtalab, Adam Tauman Kalai, Christian Borgs, Jennifer T. Chayes
2019	C	`conf`	Algorithmic Greenlining: An Approach to Increase Diversity. AIES Christian Borgs, Jennifer T. Chayes, Nika Haghtalab, Adam Tauman Kalai, Ellen Vitercik
2019	—	`conf`	Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAT Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
2019	J	`jnl`	Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. CoRR Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
2019	J	`jnl`	Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops. CoRR Limor Gultchin, Genevieve Patterson, Nancy Baym, Nathaniel Swinger, Adam Tauman Kalai
2019	A*	`conf`	Learning to Prune: Speeding up Repeated Computations. COLT Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
2019	J	`jnl`	Learning to Prune: Speeding up Repeated Computations. CoRR Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
2019	J	`jnl`	The Disparate Equilibria of Algorithmic Decision Making when Individuals Invest Rationally. CoRR Lydia T. Liu, Ashia Wilson, Nika Haghtalab, Adam Tauman Kalai, Christian Borgs, Jennifer T. Chayes
2019	C	`conf`	What are the Biases in My Word Embedding? AIES Nathaniel Swinger, Maria De-Arteaga, Neil Thomas Heffernan IV, Mark D. M. Leiserson, Adam Tauman Kalai
2019	J	`jnl`	What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. CoRR Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai
2018	A*	`conf`	Actively Avoiding Nonsense in Generative Models. COLT Steve Hanneke, Adam Tauman Kalai, Gautam Kamath, Christos Tzamos
2018	—	`conf`	Decoupled Classifiers for Group-Fair and Efficient Machine Learning. FAT Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, Mark D. M. Leiserson
2018	A*	`conf`	Glass-Box Program Synthesis: A Machine Learning Approach. AAAI Konstantina Christakopoulou, Adam Tauman Kalai
2018	B	`conf`	Usability of Humanly Computable Passwords. HCOMP Samira Samadi, Santosh S. Vempala, Adam Tauman Kalai
2018	J	`jnl`	What are the biases in my word embedding? CoRR Nathaniel Swinger, Maria De-Arteaga, Neil Thomas Heffernan IV, Mark D. M. Leiserson, Adam Tauman Kalai
2018	J	`jnl`	When optimizing nonlinear objectives is no harder than linear objectives. CoRR Daniel Alabi, Nicole Immorlica, Adam Tauman Kalai
2017	J	`jnl`	Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context. CoRR Shyam Upadhyay, Kai-Wei Chang, Matt Taddy, Adam Tauman Kalai, James Y. Zou
2017	J	`jnl`	Counterfactual Language Model Adaptation for Suggesting Phrases. CoRR Kenneth C. Arnold, Kai-Wei Chang, Adam Tauman Kalai
2017	J	`jnl`	Decoupled classifiers for fair and efficient machine learning. CoRR Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, Max D. M. Leiserson
2017	A*	`conf`	Designing and Evaluating Livefonts. UIST Danielle Bragg, Shiri Azenkot, Kevin Larson, Ann Bessemans, Adam Tauman Kalai
2017	J	`jnl`	Glass-Box Program Synthesis: A Machine Learning Approach. CoRR Konstantina Christakopoulou, Adam Tauman Kalai
2017	—	`conf`	Learning to Suggest Phrases. AAAI Workshops Kenneth Charles Arnold, Kai-Wei Chang, Adam Tauman Kalai
2017	B	`ed.`	Proceedings of the Fifth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2017, 23-26 October 2017, Québec City, Québec, Canada. HCOMP Steven Dow, Adam Tauman Kalai
2017	J	`jnl`	Usability of Humanly Computable Passwords. CoRR Samira Samadi, Santosh S. Vempala, Adam Tauman Kalai
2016	—	`conf`	Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. NIPS Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai
2016	J	`jnl`	Meta-Unsupervised-Learning: A supervised approach to unsupervised learning. CoRR Vikas K. Garg, Adam Tauman Kalai
2016	A*	`conf`	On Suggesting Phrases vs. Predicting Words for Mobile Text Composition. UIST Kenneth C. Arnold, Krzysztof Z. Gajos, Adam Tauman Kalai
2016	J	`jnl`	Quantifying and Reducing Stereotypes in Word Embeddings. CoRR Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai
2016	A*	`conf`	Reading and Learning Smartfonts. UIST Danielle Bragg, Shiri Azenkot, Adam Tauman Kalai
2015	B	`conf`	Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons. HCOMP James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai
2015	J	`jnl`	Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons. CoRR James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai
2015	A*	`conf`	Matching and Grokking: Approaches to Personalized Crowdsourcing. IJCAI Peter Organisciak, Jaime Teevan, Susan T. Dumais, Robert C. Miller, Adam Tauman Kalai
2014	B	`conf`	A Crowd of Your Own: Crowdsourcing for On-Demand Personalization. HCOMP Peter Organisciak, Jaime Teevan, Susan T. Dumais, Robert C. Miller, Adam Tauman Kalai
2013	—	`conf`	Personalized Human Computation. HCOMP (Works in Progress / Demos) Peter Organisciak, Jaime Teevan, Susan T. Dumais, Robert C. Miller, Adam Tauman Kalai
2012	J	`jnl`	Disentangling Gaussians. Commun. ACM Adam Tauman Kalai, Ankur Moitra, Gregory Valiant
2012	J	`jnl`	Reliable agnostic learning. J. Comput. Syst. Sci. Adam Tauman Kalai, Varun Kanade, Yishay Mansour
2012	J	`jnl`	Textual Features for Programming by Example CoRR Aditya Krishna Menon, Omer Tamuz, Sumit Gulwani, Butler W. Lampson, Adam Tauman Kalai
2011	J	`jnl`	Adaptively Learning the Crowd Kernel CoRR Omer Tamuz, Ce Liu, Serge J. Belongie, Ohad Shamir, Adam Tauman Kalai
2011	A	`conf`	Compression without a common prior: an information-theoretic justification for ambiguity in language. ICS Brendan Juba, Adam Tauman Kalai, Sanjeev Khanna, Madhu Sudan
2011	J	`jnl`	Dueling Algorithms CoRR Nicole Immorlica, Adam Tauman Kalai, Brendan Lucier, Ankur Moitra, Andrew Postlewaite, Moshe Tennenholtz
2011	A*	`conf`	Dueling algorithms. STOC Nicole Immorlica, Adam Tauman Kalai, Brendan Lucier, Ankur Moitra, Andrew Postlewaite, Moshe Tennenholtz
2011	J	`jnl`	Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression CoRR Sham M. Kakade, Adam Tauman Kalai, Varun Kanade, Ohad Shamir
2010	—	`conf`	A Novel Approach to Propagating Distrust. WINE Christian Borgs, Jennifer T. Chayes, Adam Tauman Kalai, Azarakhsh Malekian, Moshe Tennenholtz
2010	J	`jnl`	A commitment folk theorem. Games Econ. Behav. Adam Tauman Kalai, Ehud Kalai, Ehud Lehrer, Dov Samet
2010	A*	`ed.`	COLT 2010 - The 23rd Conference on Learning Theory, Haifa, Israel, June 27-29, 2010 COLT Adam Tauman Kalai, Mehryar Mohri
2010	A*	`conf`	Cooperation and competition in strategic games with private information. EC Adam Tauman Kalai, Ehud Kalai
2010	A*	`conf`	Efficiently learning mixtures of two Gaussians. STOC Adam Tauman Kalai, Ankur Moitra, Gregory Valiant
2010	J	`jnl`	The myth of the Folk Theorem. Games Econ. Behav. Christian Borgs, Jennifer T. Chayes, Nicole Immorlica, Adam Tauman Kalai, Vahab S. Mirrokni, Christos H. Papadimitriou
2009	J	`jnl`	Analysis of Perceptron-Based Active Learning. J. Mach. Learn. Res. Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni
2009	A*	`conf`	Learning and Smoothed Analysis. FOCS Adam Tauman Kalai, Alex Samorodnitsky, Shang-Hua Teng
2009	J	`jnl`	Playing Games with Approximation Algorithms. SIAM J. Comput. Sham M. Kakade, Adam Tauman Kalai, Katrina Ligett
2009	A*	`conf`	Reliable Agnostic Learning. COLT Adam Tauman Kalai, Varun Kanade, Yishay Mansour
2009	A*	`conf`	The Isotron Algorithm: High-Dimensional Isotonic Regression. COLT Adam Tauman Kalai, Ravi Sastry
2008	J	`jnl`	Agnostically Learning Halfspaces. SIAM J. Comput. Adam Tauman Kalai, Adam R. Klivans, Yishay Mansour, Rocco A. Servedio
2008	A*	`conf`	Agnostically learning decision trees. STOC Parikshit Gopalan, Adam Tauman Kalai, Adam R. Klivans
2008	J	`jnl`	Decision trees are PAC-learnable from most product distributions: a smoothed analysis CoRR Adam Tauman Kalai, Shang-Hua Teng
2008	A*	`conf`	On agnostic boosting and parity learning. STOC Adam Tauman Kalai, Yishay Mansour, Elad Verbin
2008	A*	`conf`	The myth of the folk theorem. STOC Christian Borgs, Jennifer T. Chayes, Nicole Immorlica, Adam Tauman Kalai, Vahab S. Mirrokni, Christos H. Papadimitriou
2007	A*	`conf`	Learning Nested Halfspaces and Uphill Decision Trees. COLT Adam Tauman Kalai
2007	A*	`conf`	Playing games with approximation algorithms. STOC Sham M. Kakade, Adam Tauman Kalai, Katrina Ligett
2006	—	`conf`	An Approach to Bounded Rationality. NIPS Eli Ben-Sasson, Adam Tauman Kalai, Ehud Kalai
2006	J	`jnl`	Simulated Annealing for Convex Optimization. Math. Oper. Res. Adam Tauman Kalai, Santosh S. Vempala
2005	A*	`conf`	Agnostically Learning Halfspaces. FOCS Adam Tauman Kalai, Adam R. Klivans, Yishay Mansour, Rocco A. Servedio
2005	A*	`conf`	Analysis of Perceptron-Based Active Learning. COLT Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni
2005	J	`jnl`	Boosting in the presence of noise. J. Comput. Syst. Sci. Adam Tauman Kalai, Rocco A. Servedio
2005	J	`jnl`	Efficient algorithms for online decision problems. J. Comput. Syst. Sci. Adam Tauman Kalai, Santosh S. Vempala
2005	A*	`conf`	Online convex optimization in the bandit setting: gradient descent without a gradient. SODA Abraham Flaxman, Adam Tauman Kalai, H. Brendan McMahan
2004	J	`jnl`	Online convex optimization in the bandit setting: gradient descent without a gradient CoRR Abraham Flaxman, Adam Tauman Kalai, H. Brendan McMahan
2003	J	`jnl`	Admission Control to Minimize Rejections. Internet Math. Avrim Blum, Adam Tauman Kalai, Jon M. Kleinberg