VINCENT: Validated Interaction Network for Cross-drug Explanation of Therapeutics

arXiv:2608.25841 · cs.LG, cs.AI · Submitted 2026-08-26 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-08-26

Updated: 2026-08-26

Comments: 18 pages, 4 figures

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

Terminology

• Calibration — 11× in this paper · explained in 7 episodes
• Core — 11× in this paper · explained in 2 episodes
• Benchmark — 10× in this paper · explained in 2 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Regularization — 4× in this paper · explained in 3 episodes
• AUC — 3× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Adaptation — 3× in this paper · explained in 1 episode
• Clustering — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Computational Biology — 2× in this paper · explained in 2 episodes
• Distribution Shift — 2× in this paper · explained in 6 episodes
• Explainability — 2× in this paper · explained in 3 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Provenance — 2× in this paper · explained in 4 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Architectural Adaptation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Graceful Degradation — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Spectral clustering — 1× in this paper · explained in 2 episodes

Sources

• Interpretable Drug Synergy Prediction with Graph Neural Networks for Human-AI Collaboration in Healthcare

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: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks