XAI

Papers

Self-Explanatory Retrieval-Augmented Generation for SDG Evidence Identification (pdf)
D. Garigliotti
Accepted in the International Workshop on AI Services and Applications (AISA) co-located with the Conceptual Modeling (ER) Conference, 2024

Optimal Robust Simplifications for Explaining Time Series Classifications (pdf)
J.A. Telle, C. Ferri, B. Håvardstun
Accepted in the Explainable AI for Time Series and Data Streams Workshop (TempXAI) co-located with ECML-PKDD Conference, 2024

On the implications of data contamination for Information Retrieval systems (pdf)
D. Garigliotti
Accepted in the International Workshop on Data-Centric Artificial Intelligence (DEARING) co-located with ECML-PKDD Conference, 2024

Explaining LLM-based Question Answering via the self-interpretations of a model (pdf)
D. Garigliotti
Accepted in the International Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence (AIMLAI) co-located with ECML-PKDD Conference, 2024

EquinorQA: Large Language Models for Question Answering over proprietary data (pdf)
D. Garigliotti, B. Johansen, J. Vigerust Kallestad, S. Cho, C. Ferri
Accepted in the Conference on Prestigious Applications of Intelligent Systems (PAIS) co-located with ECAI Conference, 2024

Confounders in Instance Variation for the Analysis of Data Contamination (pdf)
B. Mehrbakhsh, D. Garigliotti, F. Martínez-Plumed, J. Hernández-Orallo
Accepted in the Contaminated Data Workshop (CONDA) co-located with ACL Conference, 2024

SDG target detection in environmental reports using Retrieval-augmented Generation with LLMs (pdf)
D. Garigliotti
Accepted in the Natural Language Processing meets Climate Change Workshop (ClimateNLP) co-located with ACL Conference, 2024

An Interactive Tool for Interpretability of Time Series Classification (video)
B. Håvardstun, C. Ferri, J.A. Telle
Accepted in the ECML PKDD Demo Track, 2024

On a Combinatorial Problem Arising in Machine Teaching (pdf)
B. Håvardstun, J. Kratochvíl, J. Sunde, J.A. Telle
Accepted in the International Conference on Machine Learning, 2024

XAI for Time Series Classification: Evaluating the Benefits of Model Inspection for End-Users (pdf)
B. Håvardstun, C. Ferri, K. Flikka, J.A. Telle
Accepted in the World Conference on eXplainable Artificial Intelligence, 2024

MAP- and MLE-Based Teaching (pdf)
H. Simon, J.A.Telle
Accepted in the Journal of Machine Learning Research, 2024

When Redundancy Matters: Machine Teaching of Representations (pdf)
C. Ferri, D. Garigliotti, B. Håvardstun, J. Hernández-Orallo, J.A. Telle
arxiv preprint, 2024

A historical perspective of biomedical explainable AI research (pdf)
C. Ferri et al.
Patterns, 2023

XAI with Machine Teaching when Humans Are (Not) Informed about the Irrelevant Features (pdf)
B. Håvardstun, C. Ferri, J. Hernández-Orallo, P. Parviainen, J.A. Telle
European Conference on Machine Learning, ECML 2023

Heuristic search of optimal machine teaching curricula (pdf)
M. Garcia-Piqueras, J. Hernández-Orallo
Machine Learning, 1-32, 2023

Non-Cheating Teaching Revisited: A New Probabilistic Machine Teaching Model (pdf)
C. Ferri, J. Hernández-Orallo, J.A. Telle
International Joint Conference on Artificial Intelligence, IJCAI 2022

On the trade-off between fidelity and teaching complexity (pdf)
B. Håvardstun, C. Ferri, J. Hernández-Orallo, P. Parviainen, J.A. Telle
11th International Workshop on Approaches and Applications of Inductive Programming (AAIP), IJCLR 2022

Conditional teaching size (pdf)
M. Garcia-Piqueras, J. Hernández-Orallo
arXiv preprint, 2021

Teaching and explanations: aligning priors between machines and humans (link)
J. Hernández-Orallo, C. Ferri
Human-Like Machine Intelligence, 171-198, 2021

Optimal Teaching Curricula with Compositional Simplicity Priors (pdf)
M. Garcia-Piqueras, J. Hernández-Orallo
European Conference on Machine Learning, ECML 2021

Finite and Confident Teaching in Expectation: Sampling from Infinite Concept Classes (pdf)
J. Hernández-Orallo, J.A. Telle
European Conference on Artificial Intelligence, ECAI 2020

Teaching explanations by examples (pdf)
C. Ferri, J. Hernández-Orallo, J.A. Telle
MI21-HLC Machine Intelligence workshop on Human-Like Computing, 2019

The Teaching Size: Computable Teachers and Learners for Universal Languages (link)
J.A. Telle, J. Hernández-Orallo, C. Ferri
Machine Learning Journal, 2019

Finite biased teaching with infinite concept classes (pdf)
J. Hernández-Orallo, J.A. Telle
arXiv preprint, 2018