Lehman, Joel

An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

Liu, R., Lehman, J., Molino, P., Such, F. P., Frank, E., Sergeev, A., & Yosinski, J. (2018) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 784

First return, then explore

Ecoffet, A., Huizinga, J., Lehman, J., Stanley, K. O., & Clune, J. (2021) · Nature

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 330

Multi-Agent Risks from Advanced AI

Hammond, L., Chan, A., Clifton, J., Hoelscher-Obermaier, J., Khan, A., McLean, E., Smith, C., Barfuss, W., Foerster, J., Gavenčiak, T., et al. (2025) · arXiv

Ethics and Social Impacts of AIMulti-Agent Systems and Negotiation

Cited by 305

Go-Explore: a New Approach for Hard-Exploration Problems

Ecoffet, A., Huizinga, J., Lehman, J., Stanley, K. O., & Clune, J. (2019) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 205

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

Lehman, J., Clune, J., Misevic, D., Adami, C., Altenberg, L., Beaulieu, J., Bentley, P. J., Bernard, S., Beslon, G., Bryson, D. M., et al. (2020) · Artificial Life

Evolutionary Algorithms and ApplicationsEvolution and Genetic Dynamics

Cited by 181

Why Greatness Cannot Be Planned: The Myth of the Objective

Stanley, K. O., & Lehman, J. (2015) · Springer eBooks

Leadership, Courage, and Heroism StudiesEducation, Philosophy, and Society

Cited by 139

Language Model Crossover: Variation through Few-Shot Prompting

Meyerson, E., Nelson, M. J., Bradley, H., Gaier, A., Moradi, A., Hoover, A. K., & Lehman, J. (2024) · ACM Transactions on Evolutionary Learning and Optimization

Evolutionary Algorithms and ApplicationsTopic Modeling

Cited by 75

Language model crossover: Variation through few-shot prompting

Meyerson, E., Nelson, M. J., Bradley, H., Gaier, A., Moradi, A., Hoover, A. K., & Lehman, J. (2023) · arXiv

Evolutionary Algorithms and ApplicationsTopic Modeling

Cited by 75

Evolution through Large Models

Lehman, J., Gordon, J., Jain, S., Ndousse, K., Yeh, C., & Stanley, K. O. (2022) · arXiv

Evolutionary Algorithms and ApplicationsSoftware Engineering Research

Cited by 74

Evolution Through Large Models

Lehman, J., Gordon, J., Jain, S., Ndousse, K., Yeh, C., & Stanley, K. O. (2024) · Genetic and Evolutionary Computation

Evolutionary Algorithms and ApplicationsSoftware Engineering Research

Cited by 74

POET: open-ended coevolution of environments and their optimized solutions

Wang, R., Lehman, J., Clune, J., & Stanley, K. O. (2019) · Proceedings of the Genetic and Evolutionary Computation Conference

Evolutionary Algorithms and ApplicationsReinforcement Learning in Robotics

Cited by 61

The Ethics of Advanced AI Assistants

Gabriel, I., Manzini, A., Keeling, G., Hendricks, L. A., Rieser, V., Iqbal, H., Tomašev, N., Ktena, I., Kenton, Z., Rodriguez, M., et al. (2024) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 57

Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions

Wang, R., Lehman, J., Rawal, A., Zhi, J., Li, Y., Clune, J., & Stanley, K. O. (2020) · arXiv

Reinforcement Learning in RoboticsEvolutionary Algorithms and Applications

Cited by 53

The OpenELM Library: Leveraging Progress in Language Models for Novel Evolutionary Algorithms

Bradley, H., Fan, H., Galanos, T., Zhou, R., Scott, D., & Lehman, J. (2024) · Genetic and Evolutionary Computation

Evolutionary Algorithms and ApplicationsMetaheuristic Optimization Algorithms Research

Cited by 19

Open Questions in Creating Safe Open-ended AI: Tensions Between Control and Creativity

Ecoffet, A., Clune, J., & Lehman, J. (2020) · The 2020 Conference on Artificial Life

Ethics and Social Impacts of AIEvolutionary Algorithms and Applications

Cited by 6

Evolutionary Computation and AI Safety: Research Problems Impeding Routine and Safe Real-world Application of Evolution

Lehman, J. (2019) · arXiv

Ethics and Social Impacts of AIEvolutionary Algorithms and Applications

Cited by 3

Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis

Kumar, A., Clune, J., Lehman, J., & Stanley, K. O. (2025) · arXiv

Neural Networks and ApplicationsEvolutionary Algorithms and Applications

Cited by 2