most citedISCUTE: Instance Segmentation of Cables Using Text Embedding

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.RO2024

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…

cs.CV20241 cited

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…

cs.LG2024

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…

cs.SI2024

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…

cs.LG2024

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…