Cover Image

Foundations of Interpretable Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Barbiero, Pietro, Zarlenga, Mateo Espinosa, Termine, Alberto, Jamnik, Mateja, Marra, Giuseppe
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Actionable Interpretability Must Be Defined in Terms of Symmetries
by: Barbiero, Pietro, et al.
Published: (2026)

Interpretable Neural-Symbolic Concept Reasoning
by: Barbiero, Pietro, et al.
Published: (2023)

Neural Interpretable Reasoning
by: Barbiero, Pietro, et al.
Published: (2025)

Prototype-Grounded Concept Models for Verifiable Concept Alignment
by: Colamonaco, Stefano, et al.
Published: (2026)

Relational Concept Bottleneck Models
by: Barbiero, Pietro, et al.
Published: (2023)

Counterfactual Explanations for Clustering Models
by: Spagnol, Aurora, et al.
Published: (2024)

Hierarchical Concept-based Interpretable Models
by: Hill, Oscar, et al.
Published: (2026)

Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts
by: Zarlenga, Mateo Espinosa, et al.
Published: (2025)

Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning
by: Dominici, Gabriele, et al.
Published: (2024)

Towards Foundation Models for Consensus Rank Aggregation
by: Jin, Yijun, et al.
Published: (2026)

Position: Leverage Foundational Models for Black-Box Optimization
by: Song, Xingyou, et al.
Published: (2024)

Synaptic Activation and Dual Liquid Dynamics for Interpretable Bio-Inspired Models
by: Farsang, Mónika, et al.
Published: (2026)

Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science
by: Yu, Runlong, et al.
Published: (2025)

Digging Deeper: Learning Multi-Level Concept Hierarchies
by: Hill, Oscar, et al.
Published: (2026)

Interpretable Fine-Gray Deep Survival Model for Competing Risks: Predicting Post-Discharge Foot Complications for Diabetic Patients in Ontario
by: Ramachandram, Dhanesh, et al.
Published: (2025)

Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applications
by: Minhas, Mishal Fatima, et al.
Published: (2024)

REACT: Revealing Evolutionary Action Consequence Trajectories for Interpretable Reinforcement Learning
by: Altmann, Philipp, et al.
Published: (2024)

Evolving Features vs Evolving Entire Trees with GP for Interpretable Survival Analysis
by: Schlender, Thalea, et al.
Published: (2026)

Evolutionary Developmental Biology Can Serve as the Conceptual Foundation for a New Design Paradigm in Artificial Intelligence
by: Erden, Zeki Doruk, et al.
Published: (2025)

Balancing Interpretability and Performance in Motor Imagery EEG Classification: A Comparative Study of ANFIS-FBCSP-PSO and EEGNet
by: Aktar, Farjana, et al.
Published: (2025)

Projective Kolmogorov Arnold Neural Networks (P-KANs): Entropy-Driven Functional Space Discovery for Interpretable Machine Learning
by: Poole, Alastair, et al.
Published: (2025)

Sheaf Neural Networks and biomedical applications
by: Mehrab, Aneeqa, et al.
Published: (2026)

Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models
by: Kruschel, Sven, et al.
Published: (2024)

Do Concept Bottleneck Models Respect Localities?
by: Raman, Naveen, et al.
Published: (2024)

Genetic Generalized Additive Models
by: Shankar, Kaaustaaub, et al.
Published: (2026)

Nonparametric Modern Hopfield Models
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)

Surrogate Benchmarks for Model Merging Optimization
by: Akizuki, Rio, et al.
Published: (2025)

Large Language Models As Evolution Strategies
by: Lange, Robert Tjarko, et al.
Published: (2024)

Do Language Models Use Their Depth Efficiently?
by: Csordás, Róbert, et al.
Published: (2025)

Form Follows Function: Recursive Stem Model
by: Hakimi, Navid
Published: (2026)

A Resource Model For Neural Scaling Law
by: Song, Jinyeop, et al.
Published: (2024)

Heuristically Adaptive Diffusion-Model Evolutionary Strategy
by: Hartl, Benedikt, et al.
Published: (2024)

Offline Model-Based Optimization by Learning to Rank
by: Tan, Rong-Xi, et al.
Published: (2024)

Parallelization of Non-linear State-Space Models: Scaling Up Liquid-Resistance Liquid-Capacitance Networks for Efficient Sequence Modeling
by: Farsang, Mónika, et al.
Published: (2025)

EOE: Evolutionary Optimization of Experts for Training Language Models
by: Chen, Yingshi
Published: (2025)

Mergenetic: a Simple Evolutionary Model Merging Library
by: Minut, Adrian Robert, et al.
Published: (2025)

NNGPT: Rethinking AutoML with Large Language Models
by: Kochnev, Roman, et al.
Published: (2025)

FedAvgen: Metadata for Model Aggregation In Communication Systems
by: Kiggundu, Anthony, et al.
Published: (2025)

Q-S5: Towards Quantized State Space Models
by: Abreu, Steven, et al.
Published: (2024)

Training Green AI Models Using Elite Samples
by: Alswaitti, Mohammed, et al.
Published: (2024)