7 papers
GReFEM: Multimodal LLMs as Zero-Shot Semantic Assistants for Physics-Guided 3D Mesh Refinement
Kartik Bali, Mahish K. Guru, Christian J Cyron +1
Adaptive volumetric finite element meshing is a critical step in computer-aided engineering and analysis that dictates the computational budget of a given problem. It traditionally…
MV-GEL: Language-Driven Multi-View Geometric Entity Localization on Meshes
Kartik Bali, Roland Aydin
Identifying and grounding precise geometric entities, such as edges, planar regions, and curved surfaces within 3D objects, is foundational to computer-aided design (CAD), robotic…
Enhancing the quality of gauge images captured in smoke and haze scenes through deep learning
Oscar H. RamÃrez-Agudelo, Akshay N. Shewatkar, Edoardo Milana +2
Images captured in hazy and smoky environments suffer from reduced visibility, posing a challenge when monitoring infrastructures and hindering emergency services during critical s…
Automating modeling in mechanics: LLMs as designers of physics-constrained neural networks for constitutive modeling of materials
Marius Tacke, Matthias Busch, Kian Abdolazizi +4
Large language model (LLM)-based agentic frameworks increasingly adopt the paradigm of dynamically generating task-specific agents. We suggest that not only agents but also special…
T-matrix representation of optical scattering response: Suggestion for a data format
Nigar Asadova, Karim Achouri, Kristian Arjas +39
The transition matrix, frequently abbreviated as T-matrix, contains the complete information in a linear approximation of how a spatially localized object scatters an incident fiel…
Code and Pixels: Multi-Modal Contrastive Pre-training for Enhanced Tabular Data Analysis
Kankana Roy, Lars Krämer, Sebastian Domaschke +4
Learning from tabular data is of paramount importance, as it complements the conventional analysis of image and video data by providing a rich source of structured information that…