Cover Image

The Geometric Alignment Tax: Tokenization vs. Continuous Geometry in Scientific Foundation Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Raju, Prashant C.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Information Theory Quantitative Methods
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Geometric Stability: The Missing Axis of Representations
by: Raju, Prashant C.
Published: (2026)

Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification
by: Vollenweider, Michael, et al.
Published: (2024)

A Comparative Analysis of the Ensemble Methods for Drug Design
by: Davronova, Rifkat, et al.
Published: (2020)

Approximating mutual information of high-dimensional variables using learned representations
by: Gowri, Gokul, et al.
Published: (2024)

EXAONE Path 2.5: Pathology Foundation Model with Multi-Omics Alignment
by: Yun, Juseung, et al.
Published: (2025)

A Graph Based Raman Spectral Processing Technique for Exosome Classification
by: Ngo, Vuong M., et al.
Published: (2025)

From Syntax to Semantics: Geometric Stability as the Missing Axis of Perturbation Biology
by: Raju, Prashant C.
Published: (2026)

Prot2Token: A Unified Framework for Protein Modeling via Next-Token Prediction
by: Pourmirzaei, Mahdi, et al.
Published: (2025)

Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress
by: Raju, Prashant C.
Published: (2026)

What Topological and Geometric Structure Do Biological Foundation Models Learn? Evidence from 141 Hypotheses
by: Kendiukhov, Ihor
Published: (2026)

HIGHT: Hierarchical Graph Tokenization for Molecule-Language Alignment
by: Chen, Yongqiang, et al.
Published: (2024)

Pearl: A Foundation Model for Placing Every Atom in the Right Location
by: Genesis Research Team, et al.
Published: (2025)

Better Models, Faster Training: Sigmoid Attention for single-cell Foundation Models
by: Sadashivaiah, Vijay, et al.
Published: (2026)

Uncertainty-Guided Model Selection for Tabular Foundation Models in Biomolecule Efficacy Prediction
by: Li, Jie, et al.
Published: (2025)

Improved prediction of ligand-protein binding affinities by meta-modeling
by: Lee, Ho-Joon, et al.
Published: (2023)

Character-level Tokenizations as Powerful Inductive Biases for RNA Foundational Models
by: Morales-Pastor, Adrián, et al.
Published: (2024)

Foundation Models for Environmental Science: A Survey of Emerging Frontiers
by: Yu, Runlong, et al.
Published: (2025)

MS2MetGAN: Latent-space adversarial training for metabolite-spectrum matching in MS/MS database search
by: Tsai, Meng, et al.
Published: (2026)

SGUQ: Staged Graph Convolution Neural Network for Alzheimer's Disease Diagnosis using Multi-Omics Data
by: Tao, Liang, et al.
Published: (2024)

ALNSynergy: a graph convolutional network with multi-representation alignment for drug synergy prediction
by: Yang, Xinxing, et al.
Published: (2023)

Multi-scale Graph Autoregressive Modeling: Molecular Property Prediction via Next Token Prediction
by: Jiang, Zhuoyang, et al.
Published: (2026)

ViroBench: Benchmarking Nucleotide Foundation Models on Viral Genomics Tasks
by: Ye, Dongxin, et al.
Published: (2026)

TEDDY: A Family Of Foundation Models For Understanding Single Cell Biology
by: Chevalier, Alexis, et al.
Published: (2025)

SMILES-Mamba: Chemical Mamba Foundation Models for Drug ADMET Prediction
by: Xu, Bohao, et al.
Published: (2024)

Multitask Multimodal Fusion with Tabular Foundation Models for Peak and Durability Prediction of Pertussis Booster Response
by: Sitani, Divya
Published: (2026)

Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks
by: Chen, Angelica, et al.
Published: (2024)

Early warning prediction: Onsager-Machlup vs Schrödinger
by: Xu, Xiaoai, et al.
Published: (2026)

Efficient Fine-Tuning of Single-Cell Foundation Models Enables Zero-Shot Molecular Perturbation Prediction
by: Maleki, Sepideh, et al.
Published: (2024)

Can Molecular Foundation Models Know What They Don't Know? A Simple Remedy with Preference Optimization
by: He, Langzhou, et al.
Published: (2025)

Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials
by: Geraci, Joseph, et al.
Published: (2025)

A Large Sensor Foundation Model Pretrained on Continuous Glucose Monitor Data for Diabetes Management
by: Luo, Junjie, et al.
Published: (2024)

Explicit Path CGR: Maintaining Sequence Fidelity in Geometric Representations
by: Ali, Sarwan
Published: (2025)

Deep Learning Framework for RNA Inverse Folding with Geometric Structure Potentials
by: Yao, Annabelle
Published: (2025)

Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation
by: Palma, Alessandro, et al.
Published: (2025)

Unbiased and Error-Detecting Combinatorial Pooling Experiments with Balanced Constant-Weight Gray Codes for Consecutive Positives Detection
by: He, Guanchen, et al.
Published: (2025)

A measurement noise scaling law for cellular representation learning
by: Gowri, Gokul, et al.
Published: (2025)

EcoCast: A Spatio-Temporal Model for Continual Biodiversity and Climate Risk Forecasting
by: Akande, Hammed A., et al.
Published: (2025)

Chem-GMNet: A Sphere-Native Geometric Transformer for Molecular Property Prediction
by: Warrier, Deepak, et al.
Published: (2026)

Predicting Drug Solubility Using Different Machine Learning Methods -- Linear Regression Model with Extracted Chemical Features vs Graph Convolutional Neural Network
by: Ho, John, et al.
Published: (2023)

From Glucose Patterns to Health Outcomes: A Generalizable Foundation Model for Continuous Glucose Monitor Data Analysis
by: Lutsker, Guy, et al.
Published: (2024)