activity
20162026
most citedMining Worse and Better Opinions. Unsupervised and Agnostic Aggregation of Online Reviews

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Human Interventions as Labels: Localizing, Steering, and (Sometimes) Editing the Computations Behind LLM Agent Failures

Cesare Zavattari, Alessandro Tommasi, Giuseppe Prencipe

When an LLM agent misbehaves, a human steps in, and that intervention is usually discarded or replayed as training data. We treat it instead as a measurement: a label pointing at t…

cs.AI2026

One Human, Agents: Audit-Budget Allocation for LLM Agent Fleets under Miscalibrated, Correlated Confidence

Cesare Zavattari, Alessandro Tommasi, Giuseppe Prencipe

A single human must audit LLM agents under a budget of audits per round, guided by self-reported confidence that may be adversarially miscalibrated and by correlated…

cs.CL2018

Who framed Roger Reindeer? De-censorship of Facebook posts by snippet classification

Fabio Del Vigna, Marinella Petrocchi, Alessandro Tommasi +2

This paper considers online news censorship and it concentrates on censorship of identities. Obfuscating identities may occur for disparate reasons, from military to judiciary ones…

cs.SI2017★ 1 cited

Mining Worse and Better Opinions. Unsupervised and Agnostic Aggregation of Online Reviews

Michela Fazzolari, Marinella Petrocchi, Alessandro Tommasi +1

In this paper, we propose a novel approach for aggregating online reviews, according to the opinions they express. Our methodology is unsupervised - due to the fact that it does no…

cs.CL2016

Semi-supervised knowledge extraction for detection of drugs and their effects

Fabio Del Vigna, Marinella Petrocchi, Alessandro Tommasi +2

New Psychoactive Substances (NPS) are drugs that lay in a grey area of legislation, since they are not internationally and officially banned, possibly leading to their not prosecut…