8 citations · 10 across the 12 of their papers we have counts for
12 papers
Towards Natural Language-Driven Assembly Using Foundation Models
Omkar Joglekar, Tal Lancewicki, Shir Kozlovsky +3
Large Language Models (LLMs) and strong vision models have enabled rapid research and development in the field of Vision-Language-Action models that enable robotic control. The mai…
ISCUTE: Instance Segmentation of Cables Using Text Embedding
Shir Kozlovsky, Omkar Joglekar, Dotan Di Castro
In the field of robotics and automation, conventional object recognition and instance segmentation methods face a formidable challenge when it comes to perceiving Deformable Linear…
SQT -- std -target
Nitsan Soffair, Dotan Di-Castro, Orly Avner +1
Std -target is a conservative, actor-critic, ensemble, -learning-based algorithm, which is based on a single key -formula: -networks standard deviation, which is an "un…
Reviving Life on the Edge: Joint Score-Based Graph Generation of Rich Edge Attributes
Nimrod Berman, Eitan Kosman, Dotan Di Castro +1
Graph generation is integral to various engineering and scientific disciplines. Nevertheless, existing methodologies tend to overlook the generation of edge attributes. However, we…
An Axiomatic Approach to Model-Agnostic Concept Explanations
Zhili Feng, Michal Moshkovitz, Dotan Di Castro +1
Concept explanation is a popular approach for examining how human-interpretable concepts impact the predictions of a model. However, most existing methods for concept explanations…
Offline Skill Graph (OSG): A Framework for Learning and Planning using Offline Reinforcement Learning Skills
Ben-ya Halevy, Yehudit Aperstein, Dotan Di Castro
Reinforcement Learning has received wide interest due to its success in competitive games. Yet, its adoption in everyday applications is limited (e.g. industrial, home, healthcare,…
AG2U -- Autonomous Grading Under Uncertainties
Yakov Miron, Yuval Goldfracht, Chana Ross +2
Surface grading, the process of leveling an uneven area containing pre-dumped sand piles, is an important task in the construction site pipeline. This labour-intensive process is o…
Towards Autonomous Grading In The Real World
Yakov Miron, Chana Ross, Yuval Goldfracht +2
In this work, we aim to tackle the problem of autonomous grading, where a dozer is required to flatten an uneven area. In addition, we explore methods for bridging the gap between…
GraphVid: It Only Takes a Few Nodes to Understand a Video
Eitan Kosman, Dotan Di Castro
We propose a concise representation of videos that encode perceptually meaningful features into graphs. With this representation, we aim to leverage the large amount of redundancie…
DUQIM-Net: Probabilistic Object Hierarchy Representation for Multi-View Manipulation
Vladimir Tchuiev, Yakov Miron, Dotan Di-Castro
Object manipulation in cluttered scenes is a difficult and important problem in robotics. To efficiently manipulate objects, it is crucial to understand their surroundings, especia…
AGPNet -- Autonomous Grading Policy Network
Chana Ross, Yakov Miron, Yuval Goldfracht +1
In this work, we establish heuristics and learning strategies for the autonomous control of a dozer grading an uneven area studded with sand piles. We formalize the problem as a Ma…
LSP : Acceleration and Regularization of Graph Neural Networks via Locality Sensitive Pruning of Graphs
Eitan Kosman, Joel Oren, Dotan Di Castro
Graph Neural Networks (GNNs) have emerged as highly successful tools for graph-related tasks. However, real-world problems involve very large graphs, and the compute resources need…