Understanding the Capabilities of Molecular Graph Neural Networks in Materials Science Through Multimodal Learning and Physical Context Encoding
Fuente:
arXiv
Saved in:
| Main Authors: | Polat, Can, Kurban, Hasan, Serpedin, Erchin, Kurban, Mustafa |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Beyond Atomic Geometry Representations in Materials Science: A Human-in-the-Loop Multimodal Framework
by: Polat, Can, et al.
Published: (2025)
by: Polat, Can, et al.
Published: (2025)
How Far Can You Grow? Characterizing the Extrapolation Frontier of Graph Generative Models for Materials Science
by: Polat, Can, et al.
Published: (2026)
by: Polat, Can, et al.
Published: (2026)
SCALAR: Quantifying Structural Hallucination, Consistency, and Reasoning Gaps in Materials Foundation Models
by: Polat, Can, et al.
Published: (2026)
by: Polat, Can, et al.
Published: (2026)
C2NP: A Benchmark for Learning Scale-Dependent Geometric Invariances in 3D Materials Generation
by: Polat, Can, et al.
Published: (2026)
by: Polat, Can, et al.
Published: (2026)
Stress-Testing Multimodal Foundation Models for Crystallographic Reasoning
by: Polat, Can, et al.
Published: (2025)
by: Polat, Can, et al.
Published: (2025)
QuantumCanvas: A Multimodal Benchmark for Visual Learning of Atomic Interactions
by: Polat, Can, et al.
Published: (2025)
by: Polat, Can, et al.
Published: (2025)
xChemAgents: Agentic AI for Explainable Quantum Chemistry
by: Polat, Can, et al.
Published: (2025)
by: Polat, Can, et al.
Published: (2025)
IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video
by: Khanbayov, Rasul, et al.
Published: (2026)
by: Khanbayov, Rasul, et al.
Published: (2026)
HalluVerse25: Fine-grained Multilingual Benchmark Dataset for LLM Hallucinations
by: Abdaljalil, Samir, et al.
Published: (2025)
by: Abdaljalil, Samir, et al.
Published: (2025)
Knowing When Not to Answer: Abstention-Aware Scientific Reasoning
by: Abdaljalil, Samir, et al.
Published: (2026)
by: Abdaljalil, Samir, et al.
Published: (2026)
Audit-of-Understanding: Posterior-Constrained Inference for Mathematical Reasoning in Language Models
by: Abdaljalil, Samir, et al.
Published: (2025)
by: Abdaljalil, Samir, et al.
Published: (2025)
Theorem-of-Thought: A Multi-Agent Framework for Abductive, Deductive, and Inductive Reasoning in Language Models
by: Abdaljalil, Samir, et al.
Published: (2025)
by: Abdaljalil, Samir, et al.
Published: (2025)
Evaluating Multilingual and Code-Switched Alignment in LLMs via Synthetic Natural Language Inference
by: Abdaljalil, Samir, et al.
Published: (2025)
by: Abdaljalil, Samir, et al.
Published: (2025)
Halluverse-M^3: A multitask multilingual benchmark for hallucination in LLMs
by: Abdaljalil, Samir, et al.
Published: (2026)
by: Abdaljalil, Samir, et al.
Published: (2026)
EMPATHIA: Multi-Faceted Human-AI Collaboration for Refugee Integration
by: Barhdadi, Mohamed Rayan, et al.
Published: (2025)
by: Barhdadi, Mohamed Rayan, et al.
Published: (2025)
4D Synchronized Fields: Motion-Language Gaussian Splatting for Temporal Scene Understanding
by: Barhdadi, Mohamed Rayan, et al.
Published: (2026)
by: Barhdadi, Mohamed Rayan, et al.
Published: (2026)
SINdex: Semantic INconsistency Index for Hallucination Detection in LLMs
by: Abdaljalil, Samir, et al.
Published: (2025)
by: Abdaljalil, Samir, et al.
Published: (2025)
In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs
by: Kaszuba, Grzegorz, et al.
Published: (2024)
by: Kaszuba, Grzegorz, et al.
Published: (2024)
Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling
by: Li, Chaojian, et al.
Published: (2025)
by: Li, Chaojian, et al.
Published: (2025)
Pre-training Graph Neural Networks with Structural Fingerprints for Materials Discovery
by: Jia, Shuyi, et al.
Published: (2025)
by: Jia, Shuyi, et al.
Published: (2025)
Learning Ordering in Crystalline Materials with Symmetry-Aware Graph Neural Networks
by: Peng, Jiayu, et al.
Published: (2024)
by: Peng, Jiayu, et al.
Published: (2024)
Exploring Various Sequential Learning Methods for Deformation History Modeling
by: Yatkin, Muhammed Adil, et al.
Published: (2025)
by: Yatkin, Muhammed Adil, et al.
Published: (2025)
Knowledge-Reuse Transfer Learning Methods in Molecular and Material Science
by: Chen, An, et al.
Published: (2024)
by: Chen, An, et al.
Published: (2024)
SAFE: A Sparse Autoencoder-Based Framework for Robust Query Enrichment and Hallucination Mitigation in LLMs
by: Abdaljalil, Samir, et al.
Published: (2025)
by: Abdaljalil, Samir, et al.
Published: (2025)
XxaCT-NN: Structure Agnostic Multimodal Learning for Materials Science
by: Subramanian, Jithendaraa, et al.
Published: (2025)
by: Subramanian, Jithendaraa, et al.
Published: (2025)
ADA-GNN: Atom-Distance-Angle Graph Neural Network for Crystal Material Property Prediction
by: Huang, Jiao, et al.
Published: (2024)
by: Huang, Jiao, et al.
Published: (2024)
MatWheel: Addressing Data Scarcity in Materials Science Through Synthetic Data
by: Li, Wentao, et al.
Published: (2025)
by: Li, Wentao, et al.
Published: (2025)
Hybrid Quantum Graph Neural Network for Molecular Property Prediction
by: Vitz, Michael, et al.
Published: (2024)
by: Vitz, Michael, et al.
Published: (2024)
Identifying Constitutive Parameters for Complex Hyperelastic Materials using Physics-Informed Neural Networks
by: Song, Siyuan, et al.
Published: (2023)
by: Song, Siyuan, et al.
Published: (2023)
Physics-Informed Neural Networks for Electrical Circuit Analysis: Applications in Dielectric Material Modeling
by: Taj, Reyhaneh
Published: (2024)
by: Taj, Reyhaneh
Published: (2024)
A New Workflow for Materials Discovery Bridging the Gap Between Experimental Databases and Graph Neural Networks
by: Schoener, Brandon, et al.
Published: (2026)
by: Schoener, Brandon, et al.
Published: (2026)
Material Property Prediction with Element Attribute Knowledge Graphs and Multimodal Representation Learning
by: Huang, Chao, et al.
Published: (2024)
by: Huang, Chao, et al.
Published: (2024)
A Critical Examination of Active Learning Workflows in Materials Science
by: Nair, Akhil S., et al.
Published: (2026)
by: Nair, Akhil S., et al.
Published: (2026)
Learning ORDER-Aware Multimodal Representations for Composite Materials Design
by: Li, Xinyao, et al.
Published: (2026)
by: Li, Xinyao, et al.
Published: (2026)
Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting
by: Cakiroglu, Mert Onur, et al.
Published: (2025)
by: Cakiroglu, Mert Onur, et al.
Published: (2025)
Bridging Text and Crystal Structures: Literature-driven Contrastive Learning for Materials Science
by: Suzuki, Yuta, et al.
Published: (2025)
by: Suzuki, Yuta, et al.
Published: (2025)
Training-Free Active Learning Framework in Materials Science with Large Language Models
by: Wang, Hongchen, et al.
Published: (2025)
by: Wang, Hongchen, et al.
Published: (2025)
Efficient and Accurate Spatial Mixing of Machine Learned Interatomic Potentials for Materials Science
by: Birks, Fraser, et al.
Published: (2025)
by: Birks, Fraser, et al.
Published: (2025)
Do Graph Neural Networks Work for High Entropy Alloys?
by: Zhang, Hengrui, et al.
Published: (2024)
by: Zhang, Hengrui, et al.
Published: (2024)
Reduced Order Modeling of Energetic Materials Using Physics-Aware Recurrent Convolutional Neural Networks in a Latent Space (LatentPARC)
by: Gray, Zoë J., et al.
Published: (2025)
by: Gray, Zoë J., et al.
Published: (2025)
Similar Items
-
Beyond Atomic Geometry Representations in Materials Science: A Human-in-the-Loop Multimodal Framework
by: Polat, Can, et al.
Published: (2025) -
How Far Can You Grow? Characterizing the Extrapolation Frontier of Graph Generative Models for Materials Science
by: Polat, Can, et al.
Published: (2026) -
SCALAR: Quantifying Structural Hallucination, Consistency, and Reasoning Gaps in Materials Foundation Models
by: Polat, Can, et al.
Published: (2026) -
C2NP: A Benchmark for Learning Scale-Dependent Geometric Invariances in 3D Materials Generation
by: Polat, Can, et al.
Published: (2026) -
Stress-Testing Multimodal Foundation Models for Crystallographic Reasoning
by: Polat, Can, et al.
Published: (2025)