Lillicrap, Timothy

Preference Distributions of Primary Motor Cortex Neurons Reflect Control Solutions Optimized for Limb Biomechanics

Lillicrap, T. P., & Scott, S. H. (2013) · Neuron

Motor Control and AdaptationMuscle activation and electromyography studies

Cited by 157

Mastering Diverse Domains through World Models

Hafner, D., Pasukonis, J., Ba, J., & Lillicrap, T. (2023) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 124

Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes

Rae, J. W., Hunt, J. J., Harley, T., Danihelka, I., Senior, A., Wayne, G., Graves, A., & Lillicrap, T. P. (2016) · arXiv

Neural Networks and ApplicationsTopic Modeling

Cited by 89

Rotational dynamics in motor cortex are consistent with a feedback controller

Kalidindi, H. T., Cross, K. P., Lillicrap, T. P., Omrani, M., Falotico, E., Sabes, P. N., & Scott, S. H. (2021) · eLife

Motor Control and AdaptationNeural dynamics and brain function

Cited by 83

Optimizing Agent Behavior over Long Time Scales by Transporting Value

Hung, C.-C., Lillicrap, T., Abramson, J., Wu, Y., Mirza, M., Carnevale, F., Ahuja, A., & Wayne, G. (2018) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 75

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

Imitating Interactive Intelligence

Abramson, J., Ahuja, A., Barr, I., Brussee, A., Carnevale, F., Cassin, M., Chhaparia, R., Clark, S., Damoc, B., Dudzik, A., et al. (2020) · arXiv

Reinforcement Learning in RoboticsSocial Robot Interaction and HRI

Cited by 43

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

Zador, A., Escola, S., Richards, B., Ölveczky, B., Bengio, Y., Boahen, K., Botvinick, M., Chklovskii, D., Churchland, A., Clopath, C., et al. (2022) · arXiv

Embodied and Extended CognitionPsychiatry, Mental Health, Neuroscience

Cited by 34

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Raposo, D., Ritter, S., Richards, B., Lillicrap, T., Humphreys, P. C., & Santoro, A. (2024) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 8

Evaluating Long-Term Memory in 3D Mazes

Pasukonis, J., Lillicrap, T., & Hafner, D. (2022) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 3

Intra-agent speech permits zero-shot task acquisition

Yan, C., Carnevale, F., Georgiev, P., Santoro, A., Guy, A., Muldal, A., Hung, C.-C., Abramson, J., Lillicrap, T., & Wayne, G. (2022) · arXiv

Speech and dialogue systemsDomain Adaptation and Few-Shot Learning

Cited by 3

AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents

Rawles, C., Clinckemaillie, S., Chang, Y., Waltz, J., Lau, G., Fair, M., Li, A., Bishop, W., Li, W., Campbell-Ajala, F., et al. (2024) · arXiv

Usability and User Interface DesignMobile and Web Applications

Cited by 3