collaborators

7 papers

cs.CL2026

Shieldstral

Antonia Calvi, Avinash Sooriyarachchi, Giada Pistilli +274

We introduce Shieldstral, a 3B-parameter policy-adaptive multimodal safety classifier that matches or outperforms models nearly 7 its size on text safety benchmarks and set…

cs.LG2026

TS-ICL: A Flexible Time-Indexed Foundation Model for Time Series via In-Context Learning

Etienne Le Naour, Tahar Nabil, Adrien Petralia

Foundation models mark a profound paradigm shift in time series modeling, with task-specific models being superseded by general-purpose zero-shot models. Yet, current approaches pr…

cs.LG2026

Investigating simple target-covariate relationships for Chronos-2 and TabPFN-TS

Gaspard Berthelier, Mariia Baranova, Andrei-Tiberiu Pantea +4

Time Series Foundation Models (TSFMs) have recently achieved state-of-the-art performance, often outperforming supervised models in zero-shot settings. Recent TSFM architectures, s…

cs.LG2026

Are Time-Indexed Foundation Models the Future of Time Series Imputation?

Etienne Le Naour, Tahar Nabil, Adrien Petralia +1

Foundation models for time series imputation remain largely unexplored. Recently, two such models, TabPFN-TS and MoTM, have emerged. These models share a common philosophy that pla…

cs.LG2025

DeviceScope: An Interactive App to Detect and Localize Appliance Patterns in Electricity Consumption Time Series

Adrien Petralia, Paul Boniol, Philippe Charpentier +1

In recent years, electricity suppliers have installed millions of smart meters worldwide to improve the management of the smart grid system. These meters collect a large amount of…

cs.LG2025

Few Labels are all you need: A Weakly Supervised Framework for Appliance Localization in Smart-Meter Series

Adrien Petralia, Paul Boniol, Philippe Charpentier +1

Improving smart grid system management is crucial in the fight against climate change, and enabling consumers to play an active role in this effort is a significant challenge for e…