1 citations · 1 across the 5 of their papers we have counts for
5 papers
LACE: Latent Visual Representation for Cross-Embodiment Learning
Yoo Sung Jang, Kanchana Ranasinghe, Cristina Mata +3
Cross-embodiment learning from human demonstrations is hindered by the visual gap between human and robot embodiments. While self-supervised learning (SSL) backbones encode rich in…
Position: Modular Memory is the Key to Continual Learning Agents
Vaggelis Dorovatas, Malte Schwerin, Andrew D. Bagdanov +21
Foundation models have transformed machine learning through large-scale pretraining and increased test-time compute. Despite surpassing human performance in several domains, these…
Iterative Compositional Data Generation for Robot Control
Anh-Quan Pham, Marcel Hussing, Shubhankar P. Patankar +3
Collecting robotic manipulation data is expensive, making it impractical to acquire demonstrations for the combinatorially large space of tasks that arise in multi-object, multi-ro…
A Systematic Study of Large Language Models for Task and Motion Planning With PDDLStream
Jorge Mendez-Mendez
While we know that large language models (LLMs) can solve some planning problems, we do not understand the extent of these capabilities for robotics. One promising direction is to…
Continual Improvement of Threshold-Based Novelty Detection
Abe Ejilemele, Jorge Mendez-Mendez
When evaluated in dynamic, open-world situations, neural networks struggle to detect unseen classes. This issue complicates the deployment of continual learners in realistic enviro…