Probabilistic Forecasting with Conditional Generative Networks via Scoring Rule Minimization. - Lorenzo Pacchiardi; Rilwan Adewoyin; Peter Dueben; Ritabrata Dutta (CoRR, 2021)

ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation. - Ritabrata Dutta; Marcel Schöngens; Lorenzo Pacchiardi; Avinash Ummadisingu; Nicole Widmer; Pierre Künzli; Jukka-Pekka Onnela; Antonietta Mira (J. Stat. Softw., 2021)

Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic. - Ritabrata Dutta; Susana N. Gomes; Dante Kalise; Lorenzo Pacchiardi (PLoS Comput. Biol., 2021)

Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization. - Lorenzo Pacchiardi; Ritabrata Dutta (CoRR, 2022)

Score Matched Neural Exponential Families for Likelihood-Free Inference. - Lorenzo Pacchiardi; Ritabrata Dutta (J. Mach. Learn. Res., 2022)

Statistical inference in generative models using scoring rules. - Lorenzo Pacchiardi (2022)

How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions. - Lorenzo Pacchiardi; Alex James Chan; Sören Mindermann; Ilan Moscovitz; Alexa Y. Pan; Yarin Gal; Owain Evans; Jan Markus Brauner (ICLR, 2024)

100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances. - Lorenzo Pacchiardi; Lucy G. Cheke; José Hernández-Orallo (CoRR, 2024)

Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers. - Lorenzo Pacchiardi; Marko Tesic; Lucy G. Cheke; José Hernández-Orallo (CoRR, 2024)

Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization. - Lorenzo Pacchiardi; Rilwan A. Adewoyin; Peter Dueben; Ritabrata Dutta (J. Mach. Learn. Res., 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)

Paradigms of AI Evaluation: Mapping Goals, Methodologies and Culture. - John Burden; Marko Tesic; Lorenzo Pacchiardi; 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)

Measuring Data Science Automation: A Survey of Evaluation Tools for AI Assistants and Agents. - Irene Testini; José Hernández-Orallo; Lorenzo Pacchiardi (CoRR, 2025)