Predicting Collision Cross Sections with GRACE: Geometric Residual Adduct Conditioning via Early-fusion

arXiv:2609.12223 · cs.LG, cs.AI, q-bio.BM · Submitted 2026-09-10 · Read on arXiv

cs.LG, cs.AI, q-bio.BM

Submitted: 2026-09-10

Updated: 2026-10-01

Comments: 35 pages, including 10 figures and 18 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Late Fusion — 26× in this paper · explained in 2 episodes
• Generalization — 25× in this paper · explained in 13 episodes
• Accuracy — 19× in this paper · explained in 1 episode
• Transformer — 9× in this paper · explained in 2 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Embeddings — 6× in this paper · explained in 2 episodes
• LoRA Adapters — 4× in this paper · explained in 3 episodes
• Ab Initio — 3× in this paper · explained in 1 episode
• Distribution Shift — 3× in this paper · explained in 6 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 4 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Graph Construction — 2× in this paper · explained in 3 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Anisotropy — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• GNNs — 1× in this paper · explained in 2 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds
• Directional Message Passing for Molecular Graphs

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