17 accepted papers
Simulation-to-real transfer remains a central challenge in robotics, as mismatches between simulated and real-world dynamics often lead to failures. While reinforcement learning offers a principled mechanism for adaptation, existing sim-to-real finetuning methods struggle with exploration and long-h…
Imitation learning has proven effective for training robots to perform complex tasks from expert human demonstrations. However, it remains limited by its reliance on high-quality, task-specific data, restricting adaptability to the diverse range of real-world object configurations and scenarios. In …
Understanding speech production both visually and kinematically can inform second language learning system designs, as well as the creation of speaking characters in video games and animations. In this work, we introduce a data-driven method to visually represent articulator motion in Magnetic Reson…
Interactions involving children span a wide range of important domains from learning to clinical diagnostic and therapeutic contexts. Automated analyses of such interactions are motivated by the need to seek accurate insights and offer scale and robustness across diverse and wide-ranging conditions.…
A major challenge in robotics is to design robust policies which enable complex and agile behaviors in the real world. On one end of the spectrum, we have model-free reinforcement learning (MFRL), which is incredibly flexible and general but often results in brittle policies. In contrast, model pred…
In order to mitigate the sample complexity of real-world reinforcement learning, common practice is to first train a policy in a simulator where samples are cheap, and then deploy this policy in the real world, with the hope that it generalizes effectively. Such \emph{direct sim2real} transfer is no…
Precise arbitrary trajectory tracking for quadrotors is challenging due to unknown nonlinear dynamics, trajectory infeasibility, and actuation limits. To tackle these challenges, we present DATT, a learning-based approach that can precisely track arbitrary, potentially infeasible trajectories in the…
Maneuverable multicamera systems offer potential benefits in abdominal minimally-invasive procedures, including multi-view scene reconstruction and optimal viewpoint capture. Effective autonomous movement and re-positioning of such systems, however, remains an open challenge due to dynamic motion co…
Document-level relation extraction (RE) poses new challenges compared to its sentence-level counterpart. One document commonly contains multiple entity pairs, and one entity pair occurs multiple times in the document associated with multiple possible relations. In this paper, we propose two novel te…
Material science synthesis procedures are a promising domain for scientific NLP, as proper modeling of these recipes could provide insight into new ways of creating materials. However, a fundamental challenge in building information extraction models for material science synthesis procedures is gett…
First-order meta-learning algorithms have been widely used in practice to learn initial model parameters that can be quickly adapted to new tasks due to their efficiency and effectiveness. However, existing studies find that meta-learner can overfit to some specific adaptation when we have heterogen…
Recent Transformer-based models such as Transformer-XL and BERT have achieved huge success on various natural language processing tasks. However, contextualized embeddings at the output layer of these powerful models tend to degenerate and occupy an anisotropic cone in the vector space, which is cal…
Deformable objects and surfaces are ubiquitous in the daily lives of humans - from the garments in fashion to soft tissues within the body. Because of this routine interaction with soft materials, humans are adept and trained in manipulation of deformable objects while avoiding irreversible damage.…
3D reconstruction and surgical tool segmentation are necessary for several advanced tasks in robot-assisted laparoscopic surgery. These tasks include vision-based force estimation, surgical guidance, and medical image registration where pre-operative data (CT or MRI scan image slices) are overlaid o…
Hand gestures are a natural component of human-human communication. Simple hand gestures are intuitive and can exhibit great lexical variety. It stands to reason that such a user input mechanism can have many benefits, including seamless interaction, intuitive control and robustness to physical cons…
Haptic technologies have made it possible for human users to interact with cyber systems not only via traditional interfaces like keyboards and mice but also by applying force and motion. With these extra information channels, how a user haptically interacts with a system potentially presents unique…
This paper presents a method of augmenting streaming point cloud data with pretouch proximity sensor information for the purposes of teleoperated grasping of transparent targets. When using commercial RGB-Depth (RGB-D) cameras, material properties can significantly affect depth measurements. In part…