4 papers
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…
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…
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…