8 papers
PREGEN: Uncovering Latent Thoughts in Composed Video Retrieval
Gabriele Serussi, David Vainshtein, Jonathan Kouchly +2
Composed Video Retrieval (CoVR) aims to retrieve a video based on a query video and a modifying text. Current CoVR methods fail to fully exploit modern Vision-Language Models (VLMs…
LLM4SFC: Sequential Function Chart Generation via Large Language Models
Ofek Glick, Vladimir Tchuiev, Marah Ghoummaid +2
While Large Language Models (LLMs) are increasingly used for synthesizing textual PLC programming languages like Structured Text (ST) code, other IEC 61131-3 standard graphical lan…
MATCH: Task-Driven Code Evaluation through Contrastive Learning
Marah Ghoummaid, Vladimir Tchuiev, Ofek Glick +2
AI-based code generation is increasingly prevalent, with GitHub Copilot estimated to generate 46% of the code on GitHub. Accurately evaluating how well generated code aligns with d…
Towards General Modality Translation with Contrastive and Predictive Latent Diffusion Bridge
Nimrod Berman, Omkar Joglekar, Eitan Kosman +2
Recent advances in generative modeling have positioned diffusion models as state-of-the-art tools for sampling from complex data distributions. While these models have shown remark…
Gradient-Free Training of Quantized Neural Networks
Noa Cohen, Omkar Joglekar, Dotan Di Castro +3
Training neural networks requires significant computational resources and energy. Methods like mixed-precision and quantization-aware training reduce bit usage, yet they still depe…
Robot Instance Segmentation with Few Annotations for Grasping
Moshe Kimhi, David Vainshtein, Chaim Baskin +1
The ability of robots to manipulate objects relies heavily on their aptitude for visual perception. In domains characterized by cluttered scenes and high object variability, most m…