Lorenzo Pacchiardi

According to our database, Lorenzo Pacchiardi authored at least 15 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

No Answer Needed: Predicting LLM Answer Accuracy from Question-Only Linear Probes.

Iván Vicente Moreno Cencerrado, Arnau Padrés Masdemont, Anton Gonzalvez Hawthorne, David Demitri Africa, Lorenzo Pacchiardi

CoRR, September, 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, Kexin Jiang Chen, Pablo A. M. Casares, Jiyun Zu, John Burden, Behzad Mehrbakhsh, David Stillwell, Manuel Cebrián, Jindong Wang, Peter Henderson, Sherry Tongshuang Wu, Patrick C. Kyllonen, Lucy Cheke, Xing Xie, José Hernández-Orallo

CoRR, March, 2025

Measuring Data Science Automation: A Survey of Evaluation Tools for AI Assistants and Agents.

Irene Testini, Lorenzo Pacchiardi, José Hernández-Orallo

Trans. Mach. Learn. Res., 2025

Paradigms of AI Evaluation: Mapping Goals, Methodologies and Culture.

John Burden, Marko Tesic, Lorenzo Pacchiardi, José Hernández-Orallo

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

PredictaBoard: Benchmarking LLM Score Predictability.

Lorenzo Pacchiardi, Konstantinos Voudouris, Ben Slater, Fernando Martínez-Plumed, José Hernández-Orallo, Lexin Zhou, Wout Schellaert

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization.

Lorenzo Pacchiardi, Rilwan A. Adewoyin, Peter Dueben, Ritabrata Dutta

J. Mach. Learn. Res., 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

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

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2022

Statistical inference in generative models using scoring rules.

Lorenzo Pacchiardi

PhD thesis, 2022

Score Matched Neural Exponential Families for Likelihood-Free Inference.

Lorenzo Pacchiardi, Ritabrata Dutta

J. Mach. Learn. Res., 2022

Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization.

Lorenzo Pacchiardi, Ritabrata Dutta

CoRR, 2022

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

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

Probabilistic Forecasting with Conditional Generative Networks via Scoring Rule Minimization.

Lorenzo Pacchiardi, Rilwan Adewoyin, Peter Dueben, Ritabrata Dutta

CoRR, 2021