Imagen de Portada

Evaluating Post-hoc Explanations of the Transformer-based Genome Language Model DNABERT-2

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Kurth, Isabel, Sarmiento, Paulo Yanez, Renard, Bernhard Y.
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation
por: Sarmiento, Paulo Yanez, et al.
Publicado: (2024)

DNABERT-2: Fine-Tuning a Genomic Language Model for Colorectal Gene Enhancer Classification
por: King, Darren, et al.
Publicado: (2025)

Unifying Post-hoc Explanations of Knowledge Graph Completions
por: Lonardi, Alessandro, et al.
Publicado: (2025)

Informative Perturbation Selection for Uncertainty-Aware Post-hoc Explanations
por: Chugh, Sumedha, et al.
Publicado: (2026)

RAW-Explainer: Post-hoc Explanations of Graph Neural Networks on Knowledge Graphs
por: Kubo, Ryoji, et al.
Publicado: (2025)

Fuzzy Logic Function as a Post-hoc Explanator of the Nonlinear Classifier
por: Klimo, Martin, et al.
Publicado: (2024)

Explanations Go Linear: Post-hoc Explainability for Tabular Data with Interpretable Meta-Encoding
por: Piaggesi, Simone, et al.
Publicado: (2025)

Harnessing Large Language Models as Post-hoc Correctors
por: Zhong, Zhiqiang, et al.
Publicado: (2024)

Post-hoc Probabilistic Vision-Language Models
por: Baumann, Anton, et al.
Publicado: (2024)

Post-hoc Stochastic Concept Bottleneck Models
por: Hoffmann, Wiktor Jan, et al.
Publicado: (2025)

TFBS-Finder: Deep Learning-based Model with DNABERT and Convolutional Networks to Predict Transcription Factor Binding Sites
por: Ghosh, Nimisha, et al.
Publicado: (2025)

Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation
por: Chun, Yongchan, et al.
Publicado: (2026)

Explanations as Bias Detectors: A Critical Study of Local Post-hoc XAI Methods for Fairness Exploration
por: Papanikou, Vasiliki, et al.
Publicado: (2025)

Identifying Drivers of Predictive Aleatoric Uncertainty
por: Iversen, Pascal, et al.
Publicado: (2023)

In Defence of Post-hoc Explainability
por: Oh, Nick
Publicado: (2024)

The Effect of Model Size on LLM Post-hoc Explainability via LIME
por: Heyen, Henning, et al.
Publicado: (2024)

Private Federated Multiclass Post-hoc Calibration
por: Maddock, Samuel, et al.
Publicado: (2025)

Could Large Language Models work as Post-hoc Explainability Tools in Credit Risk Models?
por: Geng, Wenxi, et al.
Publicado: (2026)

Implet: A Post-hoc Subsequence Explainer for Time Series Models
por: Meng, Fanyu, et al.
Publicado: (2025)

Regression for the Mean: Auto-Evaluation and Inference with Few Labels through Post-hoc Regression
por: Eyre, Benjamin, et al.
Publicado: (2024)

DNABERT-Enhancer Trained Models
por: Sathian, Rekha, et al.
Publicado: (2026)

Post-hoc Bias Scoring Is Optimal For Fair Classification
por: Chen, Wenlong, et al.
Publicado: (2023)

PXGen: A Post-hoc Explainable Method for Generative Models
por: Huang, Yen-Lung, et al.
Publicado: (2025)

Innovative Silicosis and Pneumonia Classification: Leveraging Graph Transformer Post-hoc Modeling and Ensemble Techniques
por: Bui, Bao Q., et al.
Publicado: (2024)

BaGGLS: A Bayesian Shrinkage Framework for Interpretable Modeling of Interactions in High-Dimensional Biological Data
por: Lemanczyk, Marta S., et al.
Publicado: (2025)

DeepVRegulome: DNABERT-based deep-learning framework for predicting the functional impact of short genomic variants on the human regulome
por: Dutta, Pratik, et al.
Publicado: (2025)

P-DRUM: Post-hoc Descriptor-based Residual Uncertainty Modeling for Machine Learning Potentials
por: Huang, Shih-Peng, et al.
Publicado: (2025)

GRAIL: Post-hoc Compensation by Linear Reconstruction for Compressed Networks
por: Tang, Wenwu, et al.
Publicado: (2026)

Post-hoc Self-explanation of CNNs
por: Boubekki, Ahcène, et al.
Publicado: (2026)

Interpretable Generative Models through Post-hoc Concept Bottlenecks
por: Kulkarni, Akshay, et al.
Publicado: (2025)

Unlocking Post-hoc Dataset Inference with Synthetic Data
por: Zhao, Bihe, et al.
Publicado: (2025)

Post-hoc Interpretability Illumination for Scientific Interaction Discovery
por: Zhang, Ling, et al.
Publicado: (2024)

PSEO: Optimizing Post-hoc Stacking Ensemble Through Hyperparameter Tuning
por: Xu, Beicheng, et al.
Publicado: (2025)

Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning
por: Ortega, Luis A., et al.
Publicado: (2024)

Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
por: Zhang, Qingru, et al.
Publicado: (2023)

Self-AMPLIFY: Improving Small Language Models with Self Post Hoc Explanations
por: Bhan, Milan, et al.
Publicado: (2024)

How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural Networks
por: Cattelan, Luís Felipe P., et al.
Publicado: (2023)

Understanding Post-hoc Explainers: The Case of Anchors
por: Lopardo, Gianluigi, et al.
Publicado: (2023)

TwinTrack: Post-hoc Multi-Rater Calibration for Medical Image Segmentation
por: Kirscher, Tristan, et al.
Publicado: (2026)

Improving Time Series Forecasting via Instance-aware Post-hoc Revision
por: Liu, Zhiding, et al.
Publicado: (2025)