Image de couverture de livre

Interpreting and Steering Protein Language Models through Sparse Autoencoders

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Garcia, Edith Natalia Villegas, Ansuini, Alessio
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Biomolecules
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Automated Neuron Labelling Enables Generative Steering and Interpretability in Protein Language Models
par: Banerjee, Arjun, et autres
Publié: (2025)

Steering Protein Language Models
par: Huang, Long-Kai, et autres
Publié: (2025)

Towards Interpretable Protein Structure Prediction with Sparse Autoencoders
par: Parsan, Nithin, et autres
Publié: (2025)

InterPLM: Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders
par: Simon, Elana, et autres
Publié: (2024)

Steering Generative Models with Experimental Data for Protein Fitness Optimization
par: Yang, Jason, et autres
Publié: (2025)

Flow Autoencoders are Effective Protein Tokenizers
par: Dilip, Rohit, et autres
Publié: (2025)

Structure-Informed Protein Language Model
par: Zhang, Zuobai, et autres
Publié: (2024)

Open-Source Protein Language Models for Function Prediction and Protein Design
par: Pandi, Shivasankaran Vanaja, et autres
Publié: (2024)

Energy Efficient Protein Language Models: Leveraging Small Language Models with LoRA for Controllable Protein Generation
par: Shah, Aayush, et autres
Publié: (2024)

Peptide Sequencing Via Protein Language Models
par: Pham, Thuong Le Hoai, et autres
Publié: (2024)

Structure Language Models for Protein Conformation Generation
par: Lu, Jiarui, et autres
Publié: (2024)

Diffusion Language Models Are Versatile Protein Learners
par: Wang, Xinyou, et autres
Publié: (2024)

Structural Interpretations of Protein Language Model Representations via Differentiable Graph Partitioning
par: Dutta, Siddhant, et autres
Publié: (2026)

Reverse Distillation: Consistently Scaling Protein Language Model Representations
par: Catrina, Darius, et autres
Publié: (2026)

Function-Guided Conditional Generation Using Protein Language Models with Adapters
par: Yang, Jason, et autres
Publié: (2024)

Induction Meets Biology: Mechanisms of Repeat Detection in Protein Language Models
par: Pomerants, Gal, et autres
Publié: (2026)

Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers
par: Wang, Yingheng, et autres
Publié: (2024)

ContactNet: Geometric-Based Deep Learning Model for Predicting Protein-Protein Interactions
par: Halfon, Matan, et autres
Publié: (2024)

Docking-Aware Attention: Dynamic Protein Representations through Molecular Context Integration
par: Sicherman, Amitay, et autres
Publié: (2025)

Learning Protein Structure-Function Relationships through Knowledge-guided Representation Decomposition
par: Wang, Mingqing, et autres
Publié: (2026)

Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design
par: Tagasovska, Nataša, et autres
Publié: (2024)

PETIMOT: A Novel Framework for Inferring Protein Motions from Sparse Data Using SE(3)-Equivariant Graph Neural Networks
par: Lombard, Valentin, et autres
Publié: (2025)

A Model-Centric Review of Deep Learning for Protein Design
par: Kyro, Gregory W., et autres
Publié: (2025)

Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters
par: Arts, Marloes, et autres
Publié: (2023)

OneProt: Towards Multi-Modal Protein Foundation Models
par: Flöge, Klemens, et autres
Publié: (2024)

Insights Into the Inner Workings of Transformer Models for Protein Function Prediction
par: Wenzel, Markus, et autres
Publié: (2023)

Attention Based Molecule Generation via Hierarchical Variational Autoencoder
par: Sivanesan, Divahar
Publié: (2024)

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding
par: Wu, Lirong, et autres
Publié: (2024)

Endowing Protein Language Models with Structural Knowledge
par: Chen, Dexiong, et autres
Publié: (2024)

ProteinWeaver: A Divide-and-Assembly Approach for Protein Backbone Design
par: Ma, Yiming, et autres
Publié: (2024)

Accelerating Inference in Molecular Diffusion Models with Latent Representations of Protein Structure
par: Dunn, Ian, et autres
Publié: (2023)

Adaptive Protein Tokenization
par: Dilip, Rohit, et autres
Publié: (2026)

Improving Targeted Molecule Generation through Language Model Fine-Tuning Via Reinforcement Learning
par: Ahmed, Salma J., et autres
Publié: (2024)

Rigid Protein-Protein Docking via Equivariant Elliptic-Paraboloid Interface Prediction
par: Yu, Ziyang, et autres
Publié: (2024)

Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering
par: Jiao, Shujian, et autres
Publié: (2024)

Protein Conformation Generation via Force-Guided SE(3) Diffusion Models
par: Wang, Yan, et autres
Publié: (2024)

QuickBind: A Light-Weight And Interpretable Molecular Docking Model
par: Treyde, Wojtek, et autres
Publié: (2024)

Hierarchical Multi-Label Contrastive Learning for Protein-Protein Interaction Prediction Across Organisms
par: Liu, Shiyi, et autres
Publié: (2025)

Compact Artificial Neural Network Models for Predicting Protein Residue -- RNA Base Binding
par: Selitskiy, Stanislav
Publié: (2025)

Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings
par: Sengar, Aditya, et autres
Publié: (2025)