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Long Le I'm a PhD student at the University of Pennsylvania, where my research focuses on robot learning and autonomous systems. I have worked as a Software Engineer at Google (2022), as an Intern at Robotics Institute, CMU (2021), and as an Intern at Instagram (2020). |
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ResearchI am interested in scalable robot learning. Below are my works. |
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Articulate Anything
Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton International Conference on Learning Representations (ICLR), 2025 ArXiv / Code / Website A major bottleneck in scaling robot learning in simulation is the lack of interactable 3D environments. We present a SOTA method, leveraging VLMs to automatically generate articulated 3D models from any input modality including text, real-world images, or videos. |
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Distributed Continual Learning
Long Le, Marcel Hussing, and Eric Eaton Preprint, 2024 ArXiv We study the intersection of continual and federated learning, in which independent agents face unique tasks. We develop the mathematical formulation for the setting, develop algorithms for sharing data, model weights, and modules, and provide extensive empirical results across network bandwidths, and topology. |
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A collective AI via lifelong learning and sharing at the edge
A Soltoggio et al Nature Machine Intelligence, 2024 Paper We survey approaches and challenges in developing a collaborative life-long AI system on edge devices. |
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