Lisa Lee
Cited by
Cited by
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
Dual Motion GAN for Future-Flow Embedded Video Prediction
X Liang, L Lee, W Dai, EP Xing
International Conference on Computer Vision, 2017
Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute Detection
X Liang, L Lee, E Xing
Conference on Computer Vision and Pattern Recognition, 2017
Rt-2: Vision-language-action models transfer web knowledge to robotic control
A Brohan, N Brown, J Carbajal, Y Chebotar, X Chen, K Choromanski, ...
arXiv preprint arXiv:2307.15818, 2023
Efficient Exploration via State Marginal Matching
L Lee, B Eysenbach, E Parisotto, R Salakhutdinov, S Levine
arXiv preprint arXiv:1906.05274, 2019
Multi-game decision transformers
KH Lee, O Nachum, MS Yang, L Lee, D Freeman, S Guadarrama, ...
Advances in Neural Information Processing Systems 35, 27921-27936, 2022
Gated Path Planning Networks
L Lee, E Parisotto, D Chaplot, E Xing, R Salakhutdinov
International Conference on Machine Learning (ICML), 2018
Open x-embodiment: Robotic learning datasets and rt-x models
A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ...
arXiv preprint arXiv:2310.08864, 2023
Multimodal masked autoencoders learn transferable representations
X Geng, H Liu, L Lee, D Schuurmans, S Levine, P Abbeel
arXiv preprint arXiv:2205.14204, 2022
f-irl: Inverse reinforcement learning via state marginal matching
T Ni, H Sikchi, Y Wang, T Gupta, L Lee, B Eysenbach
Conference on Robot Learning, 529-551, 2021
Gemma: Open models based on gemini research and technology
G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ...
arXiv preprint arXiv:2403.08295, 2024
Rt-2: Vision-language-action models transfer web knowledge to robotic control
B Zitkovich, T Yu, S Xu, P Xu, T Xiao, F Xia, J Wu, P Wohlhart, S Welker, ...
Conference on Robot Learning, 2165-2183, 2023
Combining LSTM and latent topic modeling for mortality prediction
Y Jo, L Lee, S Palaskar
arXiv preprint arXiv:1709.02842, 2017
Embodied Multimodal Multitask Learning
DS Chaplot, L Lee, R Salakhutdinov, D Parikh, D Batra
arXiv preprint arXiv:1902.01385, 2019
External vs. internal: an essay on machine learning agents for autonomous database management systems
A Pavlo, M Butrovich, A Joshi, L Ma, P Menon, D Van Aken, L Lee, ...
IEEE bulletin 42 (2), 2019
Instruction-following agents with jointly pre-trained vision-language models
H Liu, L Lee, K Lee, P Abbeel
Weakly-supervised reinforcement learning for controllable behavior
L Lee, B Eysenbach, RR Salakhutdinov, SS Gu, C Finn
Advances in Neural Information Processing Systems 33, 2661-2673, 2020
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
Spectral decomposition representation for reinforcement learning
T Ren, T Zhang, L Lee, JE Gonzalez, D Schuurmans, B Dai
arXiv preprint arXiv:2208.09515, 2022
Barkour: Benchmarking animal-level agility with quadruped robots
K Caluwaerts, A Iscen, JC Kew, W Yu, T Zhang, D Freeman, KH Lee, ...
arXiv preprint arXiv:2305.14654, 2023
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