48 citations · 55 across the 8 of their papers we have counts for
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cs.AI2026
Comparing Explanations is Not Enough, Explain the Change: New Standards are Needed to Explain Behavioral Shifts in Large Language Models
Martino Ciaperoni, Marzio Di Vece, Roberto Pellungrini +3
Large-scale foundation models exhibit behavioral shifts when subjected to interventions such as scaling, fine-tuning, reinforcement learning with human feedback, or in-context lear…
cs.AI2024
Bridging the Gap in Hybrid Decision-Making Systems
Federico Mazzoni, Roberto Pellungrini, Riccardo Guidotti
We introduce BRIDGET, a novel human-in-the-loop system for hybrid decision-making, aiding the user to label records from an un-labeled dataset, attempting to ``bridge the gap'' bet…