6 papers
Physics Context Builders: A Modular Framework for Physical Reasoning in Vision-Language Models
Vahid Balazadeh, Mohammadmehdi Ataei, Hyunmin Cheong +2
Physical reasoning remains a significant challenge for Vision-Language Models (VLMs). This limitation arises from an inability to translate learned knowledge into predictions about…
mPOLICE: Provable Enforcement of Multi-Region Affine Constraints in Deep Neural Networks
Mohammadmehdi Ataei, Hyunmin Cheong, Adrian Butscher
Deep neural networks are increasingly used in safety-critical domains such as robotics and scientific modeling, where strict adherence to output constraints is essential. Methods l…
Transformer-Based Interfaces for Mechanical Assembly Design: A Gear Train Case Study
Mohammadmehdi Ataei, Hyunmin Cheong, Jiwon Jun +3
Generative artificial intelligence (AI), particularly transformer-based models, presents new opportunities for automating and augmenting engineering design workflows. However, effe…
e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration
Hyunmin Cheong, Mohammadmehdi Ataei, Amir Hosein Khasahmadi +1
Deep generative models have recently shown success in solving complex engineering design problems where models predict solutions that address the design requirements specified as i…
Deep Generative Model for Mechanical System Configuration Design
Yasaman Etesam, Hyunmin Cheong, Mohammadmehdi Ataei +1
Generative AI has made remarkable progress in addressing various design challenges. One prominent area where generative AI could bring significant value is in engineering design. I…
DesignQA: A Multimodal Benchmark for Evaluating Large Language Models' Understanding of Engineering Documentation
Anna C. Doris, Daniele Grandi, Ryan Tomich +4
This research introduces DesignQA, a novel benchmark aimed at evaluating the proficiency of multimodal large language models (MLLMs) in comprehending and applying engineering requi…