Sparks of artificial general intelligence: Early experiments with gpt-4 S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ... arXiv preprint arXiv:2303.12712, 2023 | 3256 | 2023 |
Artificial intelligence and life in 2030: the one hundred year study on artificial intelligence P Stone, R Brooks, E Brynjolfsson, R Calo, O Etzioni, G Hager, ... arXiv preprint arXiv:2211.06318, 2022 | 1213 | 2022 |
Machine behaviour I Rahwan, M Cebrian, N Obradovich, J Bongard, JF Bonnefon, C Breazeal, ... Nature 568 (7753), 477-486, 2019 | 1199 | 2019 |
Software engineering for machine learning: A case study S Amershi, A Begel, C Bird, R DeLine, H Gall, E Kamar, N Nagappan, ... 2019 IEEE/ACM 41st International Conference on Software Engineering …, 2019 | 1033 | 2019 |
Does the whole exceed its parts? the effect of ai explanations on complementary team performance G Bansal, T Wu, J Zhou, R Fok, B Nushi, E Kamar, MT Ribeiro, D Weld Proceedings of the 2021 CHI conference on human factors in computing systems …, 2021 | 617 | 2021 |
Combining human and machine intelligence in large-scale crowdsourcing. E Kamar, S Hacker, E Horvitz AAMAS 12, 467-474, 2012 | 527 | 2012 |
Beyond accuracy: The role of mental models in human-AI team performance G Bansal, B Nushi, E Kamar, WS Lasecki, DS Weld, E Horvitz Proceedings of the AAAI conference on human computation and crowdsourcing 7 …, 2019 | 494 | 2019 |
Sparks of artificial general intelligence: Early experiments with GPT-4. arXiv S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ... arXiv preprint arXiv:2303.12712, 2023 | 367 | 2023 |
Toxigen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection T Hartvigsen, S Gabriel, H Palangi, M Sap, D Ray, E Kamar arXiv preprint arXiv:2203.09509, 2022 | 365 | 2022 |
Interpretable & explorable approximations of black box models H Lakkaraju, E Kamar, R Caruana, J Leskovec arXiv preprint arXiv:1707.01154, 2017 | 363 | 2017 |
Updates in human-ai teams: Understanding and addressing the performance/compatibility tradeoff G Bansal, B Nushi, E Kamar, DS Weld, WS Lasecki, E Horvitz Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 2429-2437, 2019 | 350 | 2019 |
Revolt: Collaborative crowdsourcing for labeling machine learning datasets JC Chang, S Amershi, E Kamar Proceedings of the 2017 CHI conference on human factors in computing systems …, 2017 | 339 | 2017 |
Faithful and customizable explanations of black box models H Lakkaraju, E Kamar, R Caruana, J Leskovec Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 131-138, 2019 | 336 | 2019 |
Software engineering for machine learning: a case study. In 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) S Amershi, A Begel, C Bird, R DeLine, H Gall, E Kamar, N Nagappan, ... IEEE, 2019 | 265 | 2019 |
Directions in Hybrid Intelligence: Complementing AI Systems with Human Intelligence. E Kamar IJCAI, 4070-4073, 2016 | 257 | 2016 |
Collaboration and shared plans in the open world: Studies of ridesharing E Kamar, E Horvitz Twenty-first international joint conference on artificial intelligence, 2009 | 205 | 2009 |
Identifying unknown unknowns in the open world: Representations and policies for guided exploration H Lakkaraju, E Kamar, R Caruana, E Horvitz Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 204 | 2017 |
Learning to complement humans B Wilder, E Horvitz, E Kamar arXiv preprint arXiv:2005.00582, 2020 | 194 | 2020 |
Is the most accurate ai the best teammate? optimizing ai for teamwork G Bansal, B Nushi, E Kamar, E Horvitz, DS Weld Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11405 …, 2021 | 180 | 2021 |
Volunteering versus work for pay: Incentives and tradeoffs in crowdsourcing A Mao, E Kamar, Y Chen, E Horvitz, M Schwamb, C Lintott, A Smith Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 1 …, 2013 | 179 | 2013 |