Newton Trees. - Fernando Martínez-Plumed; Vicent Estruch; César Ferri; José Hernández-Orallo; M. José Ramírez-Quintana (Australasian Conference on Artificial Intelligence, 2010)

Learning with Configurable Operators and RL-Based Heuristics. - Fernando Martínez-Plumed; César Ferri; José Hernández-Orallo; M. José Ramírez-Quintana (NFMCP, 2012)

On the definition of a general learning system with user-defined operators. - Fernando Martínez-Plumed; Cèsar Ferri Ramirez; José Hernández-Orallo; M. José Ramírez-Quintana (CoRR, 2013)

A Knowledge Growth and Consolidation Framework for Lifelong Machine Learning Systems. - Fernando Martínez-Plumed; César Ferri; José Hernández-Orallo; M. José Ramírez-Quintana (ICMLA, 2014)

Pentaho + R: An Integral View for Multidimensional Prediction Models. - Adolfo Martínez Usó; José Hernández-Orallo; M. José Ramírez-Quintana; Fernando Martínez-Plumed (CAEPIA, 2015)

Knowledge acquisition with forgetting: an incremental and developmental setting. - Fernando Martínez-Plumed; César Ferri; José Hernández-Orallo; María José Ramírez (Adapt. Behav., 2015)

Forgetting and consolidation for incremental and cumulative knowledge acquisition systems. - Fernando Martínez-Plumed; César Ferri; José Hernández-Orallo; M. José Ramírez-Quintana (CoRR, 2015)

Making Sense of Item Response Theory in Machine Learning. - Fernando Martínez-Plumed; Ricardo B. C. Prudêncio; Adolfo Martínez Usó; José Hernández-Orallo (ECAI, 2016)

Cycling Network Projects: A Decision-Making Aid Approach. - Fernando Martínez-Plumed; César Ferri; Lidia Contreras Ochando (SoGood@ECML-PKDD, 2016)

Computer models solving intelligence test problems: Progress and implications. - José Hernández-Orallo; Fernando Martínez-Plumed; Ute Schmid; Michael Siebers; David L. Dowe (Artif. Intell., 2016)

Computer Models Solving Intelligence Test Problems: Progress and Implications (Extended Abstract). - José Hernández-Orallo; Fernando Martínez-Plumed; Ute Schmid; Michael Siebers; David L. Dowe (IJCAI, 2017)

Mapping Intelligence: Requirements and Possibilities. - Sankalp Bhatnagar; Anna Alexandrova; Shahar Avin; Stephen Cave; Lucy Cheke; Matthew Crosby; Jan Feyereisl; Marta Halina; Bao Sheng Loe; Seán Ó hÉigeartaigh; Fernando Martínez-Plumed; Huw Price; et al. (PT-AI, 2017)

Modelling Machine Learning Models. - Raül Fabra-Boluda; Cèsar Ferri; José Hernández-Orallo; Fernando Martínez-Plumed; M. José Ramírez-Quintana (PT-AI, 2017)

Incremental and developmental perspectives for general-purpose learning systems. - Fernando Martínez-Plumed (Inteligencia Artif., 2017)

A New AI Evaluation Cosmos: Ready to Play the Game? - José Hernández-Orallo; Marco Baroni; Jordi Bieger; Nader Chmait; David L. Dowe; Katja Hofmann; Fernando Martínez-Plumed; Claes Strannegård; Kristinn R. Thórisson (AI Mag., 2017)

A computational analysis of general intelligence tests for evaluating cognitive development. - Fernando Martínez-Plumed; César Ferri; José Hernández-Orallo; María José Ramírez-Quintana (Cogn. Syst. Res., 2017)

CASP-DM: Context Aware Standard Process for Data Mining. - Fernando Martínez-Plumed; Lidia Contreras Ochando; César Ferri; Peter A. Flach; José Hernández-Orallo; Meelis Kull; Nicolas Lachiche; María José Ramírez-Quintana (CoRR, 2017)

Identifying the Machine Learning Family from Black-Box Models. - Raül Fabra-Boluda; Cèsar Ferri; José Hernández-Orallo; Fernando Martínez-Plumed; María José Ramírez-Quintana (CAEPIA, 2018)

The Facets of Artificial Intelligence: A Framework to Track the Evolution of AI. - Fernando Martínez-Plumed; Bao Sheng Loe; Peter A. Flach; Seán Ó hÉigeartaigh; Karina Vold; José Hernández-Orallo (IJCAI, 2018)

SALER: A Data Science Solution to Detect and Prevent Corruption in Public Administration. - Fernando Martínez-Plumed; Juan Carlos Casamayor; Cèsar Ferri; Jon Ander Gómez; Eduardo Vendrell Vidal (Nemesis/UrbReas/SoGood/IWAISe/GDM@PKDD/ECML, 2018)

Accounting for the Neglected Dimensions of AI Progress. - Fernando Martínez-Plumed; Shahar Avin; Miles Brundage; Allan Dafoe; Seán Ó hÉigeartaigh; José Hernández-Orallo (CoRR, 2018)

A multidisciplinary task-based perspective for evaluating the impact of AI autonomy and generality on the future of work. - Enrique Fernández-Macías; Emilia Gómez; José Hernández-Orallo; Bao Sheng Loe; Bertin Martens; Fernando Martínez-Plumed; Songül Tolan (CoRR, 2018)

General-purpose Declarative Inductive Programming with Domain-Specific Background Knowledge for Data Wrangling Automation. - Lidia Contreras Ochando; Cèsar Ferri; José Hernández-Orallo; Fernando Martínez-Plumed; María José Ramírez-Quintana; Susumu Katayama (CoRR, 2018)

Analysing Results from AI Benchmarks: Key Indicators and How to Obtain Them. - Fernando Martínez-Plumed; José Hernández-Orallo (CoRR, 2018)

Surveying Safety-relevant AI Characteristics. - José Hernández-Orallo; Fernando Martínez-Plumed; Shahar Avin; Seán Ó hÉigeartaigh (SafeAI@AAAI, 2019)

Automated Data Transformation with Inductive Programming and Dynamic Background Knowledge. - Lidia Contreras Ochando; Cèsar Ferri; José Hernández-Orallo; Fernando Martínez-Plumed; María José Ramírez-Quintana; Susumu Katayama (ECML/PKDD (3), 2019)

BK-ADAPT: Dynamic Background Knowledge for Automating Data Transformation. - Lidia Contreras Ochando; César Ferri; José Hernández-Orallo; Fernando Martínez-Plumed; María José Ramírez-Quintana; Susumu Katayama (ECML/PKDD (3), 2019)

Item response theory in AI: Analysing machine learning classifiers at the instance level. - Fernando Martínez-Plumed; Ricardo B. C. Prudêncio; Adolfo Martínez Usó; José Hernández-Orallo (Artif. Intell., 2019)

Fairness and Missing Values. - Fernando Martínez-Plumed; Cèsar Ferri; David Nieves; José Hernández-Orallo (CoRR, 2019)

Does AI Qualify for the Job?: A Bidirectional Model Mapping Labour and AI Intensities. - Fernando Martínez-Plumed; Songül Tolan; Annarosa Pesole; José Hernández-Orallo; Enrique Fernández-Macías; Emilia Gómez (AIES, 2020)

Family and Prejudice: A Behavioural Taxonomy of Machine Learning Techniques. - Raül Fabra-Boluda; Cèsar Ferri; Fernando Martínez-Plumed; José Hernández-Orallo; M. José Ramírez-Quintana (ECAI, 2020)

AI Paradigms and AI Safety: Mapping Artefacts and Techniques to Safety Issues. - José Hernández-Orallo; Fernando Martínez-Plumed; Shahar Avin; Jess Whittlestone; Seán Ó hÉigeartaigh (ECAI, 2020)

Tracking AI: The Capability Is (Not) Near. - Fernando Martínez-Plumed; José Hernández-Orallo; Emilia Gómez (ECAI, 2020)

Dual Indicators to Analyze AI Benchmarks: Difficulty, Discrimination, Ability, and Generality. - Fernando Martínez-Plumed; José Hernández-Orallo (IEEE Trans. Games, 2020)

Project-Based Learning for Scaffolding Data Scientists' Skills. - Fernando Martínez-Plumed; José Hernández-Orallo (ICCSE, 2021)

Compute and Energy Consumption Trends in Deep Learning Inference. - Radosvet Desislavov; Fernando Martínez-Plumed; José Hernández-Orallo (CoRR, 2021)

Editor's Note. - Amparo Alonso-Betanzos; Pedro Cabalar; Graçaliz Pereira Dimuro; Marcos García 001; José Hernández-Orallo; Raquel Hervás; Angeles Manjarés; Fernando Martínez-Plumed; Inmaculada Mora-Jiménez; Miquel Sànchez-Marrè (Int. J. Interact. Multim. Artif. Intell., 2021)

Missing the missing values: The ugly duckling of fairness in machine learning. - Fernando Martínez-Plumed; Cèsar Ferri; David Nieves; José Hernández-Orallo (Int. J. Intell. Syst., 2021)

Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks. - Songül Tolan; Annarosa Pesole; Fernando Martínez-Plumed; Enrique Fernández-Macías; José Hernández-Orallo; Emilia Gómez (J. Artif. Intell. Res., 2021)

Futures of artificial intelligence through technology readiness levels. - Fernando Martínez-Plumed; Emilia Gómez; José Hernández-Orallo (Telematics Informatics, 2021)

CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories. - Fernando Martínez-Plumed; Lidia Contreras Ochando; Cèsar Ferri; José Hernández-Orallo; Meelis Kull; Nicolas Lachiche; María José Ramírez-Quintana; Peter A. Flach (IEEE Trans. Knowl. Data Eng., 2021)

Training on the Test Set: Mapping the System-Problem Space in AI. - José Hernández-Orallo; Wout Schellaert; Fernando Martínez-Plumed (AAAI, 2022)

When AI Difficulty Is Easy: The Explanatory Power of Predicting IRT Difficulty. - Fernando Martínez-Plumed; David Castellano Falcón; Carlos Monserrat Aranda; José Hernández-Orallo (AAAI, 2022)

Robustness Testing of Machine Learning Families using Instance-Level IRT-Difficulty. - Raül Fabra-Boluda; Cèsar Ferri; Fernando Martínez-Plumed; María José Ramírez-Quintana (EBeM@IJCAI, 2022)

Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks (Extended Abstract). - Songül Tolan; Annarosa Pesole; Fernando Martínez-Plumed; Enrique Fernández-Macías; José Hernández-Orallo; Emilia Gómez (IJCAI, 2022)

Reject Before You Run: Small Assessors Anticipate Big Language Models. - Lexin Zhou; Fernando Martínez-Plumed; José Hernández-Orallo; Cèsar Ferri; Wout Schellaert (EBeM@IJCAI, 2022)

Adversarial Benchmark Evaluation Rectified by Controlling for Difficulty. - Behzad Mehrbakhsh; Fernando Martínez-Plumed; José Hernández-Orallo (ECAI, 2023)

Predictable Artificial Intelligence. - Lexin Zhou; Pablo Antonio Moreno Casares; Fernando Martínez-Plumed; John Burden; Ryan Burnell; Lucy Cheke; Cèsar Ferri; Alexandru Marcoci; Behzad Mehrbakhsh; Yael Moros-Daval; Seán Ó hÉigeartaigh; Danaja Rutar; et al. (CoRR, 2023)

Your Prompt is My Command: On Assessing the Human-Centred Generality of Multimodal Models. - Wout Schellaert; Fernando Martínez-Plumed; Karina Vold; John Burden; Pablo A. M. Casares; Bao Sheng Loe; Roi Reichart; Seán Ó hÉigeartaigh; Anna Korhonen; José Hernández-Orallo (J. Artif. Intell. Res., 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Trends in AI inference energy consumption: Beyond the performance-vs-parameter laws of deep learning. - Radosvet Desislavov; Fernando Martínez-Plumed; José Hernández-Orallo (Sustain. Comput. Informatics Syst., 2023)

Can language models automate data wrangling? - Gonzalo Jaimovitch-López; Cèsar Ferri; José Hernández-Orallo; Fernando Martínez-Plumed; María José Ramírez-Quintana (Mach. Learn., 2023)

Training Data Scientists Through Project-Based Learning. - Fernando Martínez-Plumed; José Hernández-Orallo (Rev. Iberoam. de Tecnol. del Aprendiz., 2023)

Your Prompt Is My Command: On Assessing the Human-Centred Generality of Multimodal Models (Abstract Reprint). - Wout Schellaert; Fernando Martínez-Plumed; Karina Vold; John Burden; Pablo A. M. Casares; Bao Sheng Loe; Roi Reichart; Seán Ó hÉigeartaigh; Anna Korhonen; José Hernández-Orallo (AAAI, 2024)

Confounders in Instance Variation for the Analysis of Data Contamination. - Behzad Mehrbakhsh; Darío Garigliotti; Fernando Martínez-Plumed; José Hernández-Orallo (CONDA, 2024)

Distilling the Effects of Language Model Contamination. - Behzad Mehrbakhsh; Fernando Martínez-Plumed; José Hernández-Orallo (ECAI, 2024)

Language Task Difficulty Prediction Through LLM-Annotated Meta-Features. - Yael Moros-Daval; Fernando Martínez-Plumed; José Hernández-Orallo (ECAI, 2024)

Automatic PDF Document Classification with Machine Learning. - Sócrates Llácer Luna; Darío Garigliotti; Fernando Martínez-Plumed; Cèsar Ferri Ramirez (IDEAL (1), 2024)

Noise Tolerance and Robustness Ranking in Machine Learning Models. - Cristina Padró-Ferragut; María José Ramírez-Quintana; Fernando Martínez-Plumed (IDEAL (2), 2024)

How Resilient are Language Models to Text Perturbations? - Daniel Romero-Alvarado; José Hernández-Orallo; Fernando Martínez-Plumed (IDEAL (1), 2024)

Unveiling the robustness of machine learning families. - Raül Fabra-Boluda; Cèsar Ferri; María José Ramírez-Quintana; Fernando Martínez-Plumed (Mach. Learn. Sci. Technol., 2024)

Larger and More Instructable Language Models Turned Less Reliable (Code and Data). - Lexin Zhou; Wout Schellaert; Fernando Martínez-Plumed; Yael Moros-Daval; Cèsar Ferri; José Hernández-Orallo (Zenodo, 2024)

Larger and more instructable language models become less reliable (code and data). - Lexin Zhou; Wout Schellaert; Fernando Martínez-Plumed; Yael Moros-Daval; Cèsar Ferri; José Hernández-Orallo (Zenodo, 2024)

Larger and more instructable language models become less reliable (code and data). - Lexin Zhou; Wout Schellaert; Fernando Martínez-Plumed; Yael Moros-Daval; Cèsar Ferri; José Hernández-Orallo (Zenodo, 2024)

Larger and more instructable language models become less reliable. - Lexin Zhou; Wout Schellaert; Fernando Martínez-Plumed; Yael Moros-Daval; Cèsar Ferri; José Hernández-Orallo (Nat., 2024)

PredictaBoard: Benchmarking LLM Score Predictability. - Lorenzo Pacchiardi; Konstantinos Voudouris; Ben Slater; Fernando Martínez-Plumed; José Hernández-Orallo; Lexin Zhou; Wout Schellaert (ACL (Findings), 2025)

Refining Community Detection in Social Networks: Agglomerative and Divisive Methods with Size Constraints. - Diego Vallejo-Huanga; Erlend Eindride Fasmer; Cèsar Ferri; Fernando Martínez-Plumed (MDAI, 2025)

Cracking black-box models: Revealing hidden machine learning techniques behind their predictions. - Raül Fabra-Boluda; Cèsar Ferri; José Hernández-Orallo; M. José Ramrez-Quintana; Fernando Martínez-Plumed (Intell. Data Anal., 2025)

What should an AI assessor optimise for? - Daniel Romero-Alvarado; Fernando Martínez-Plumed; José Hernández-Orallo (CoRR, 2025)

General Scales Unlock AI Evaluation with Explanatory and Predictive Power. - Lexin Zhou; Lorenzo Pacchiardi; Fernando Martínez-Plumed; Katherine M. Collins; Yael Moros-Daval; Seraphina Zhang; Qinlin Zhao; Yitian Huang; Luning Sun; Jonathan E. Prunty; Zongqian Li; Pablo Sánchez-García; et al. (CoRR, 2025)

Analysing the Predictability of Language Model Performance. - Wout Schellaert; Fernando Martínez-Plumed; José Hernández-Orallo (ACM Trans. Intell. Syst. Technol., 2025)