OxiGen: Oxidation-State-Aware Crystal Generation
cs.LG, cond-mat.mtrl-sci
Submitted: 2026-10-06
Updated: 2026-10-06
Sources
- LeMat-GenBench: A Unified Evaluation Framework for Crystal Generative Models
- Discovery and recovery of crystalline materials with property-conditioned transformers
- Constrained Decoding for Diffusion Language Models via Efficient Inference over Finite Automata
- Chemical filters for ultra-high-throughput materials screening and generation
- Crystal-GFN: sampling crystals with desirable properties and constraints
- MiAD: Mirage Atom Diffusion for De Novo Crystal Generation
- Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling
- Primal-Dual Guided Decoding for Constrained Discrete Diffusion
- Crystalite: A Lightweight Transformer for Efficient Crystal Modeling
- PLaID++: A Preference Aligned Language Model for Targeted Inorganic Materials Design
- MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks