7 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…
Beyond Data Scarcity: A Frequency-Driven Framework for Zero-Shot Forecasting
Liran Nochumsohn, Michal Moshkovitz, Orly Avner +2
Time series forecasting is critical in numerous real-world applications, requiring accurate predictions of future values based on observed patterns. While traditional forecasting t…
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…
Radar Spectra-Language Model for Automotive Scene Parsing
Mariia Pushkareva, Yuri Feldman, Csaba Domokos +2
Radar sensors are low cost, long-range, and weather-resilient. Therefore, they are widely used for driver assistance functions, and are expected to be crucial for the success of au…