most citedUnderstanding the Capabilities of Large Language Models for Automated Planning

6 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20234 cited

Legal Summarisation through LLMs: The PRODIGIT Project

Thiago Dal Pont, Federico Galli, Andrea Loreggia +3

We present some initial results of a large-scale Italian project called PRODIGIT which aims to support tax judges and lawyers through digital technology, focusing on AI. We have fo…

cs.AI2023

Value-based Fast and Slow AI Nudging

Marianna B. Ganapini, Francesco Fabiano, Lior Horesh +7

Nudging is a behavioral strategy aimed at influencing people's thoughts and actions. Nudging techniques can be found in many situations in our daily lives, and these nudging techni…

cs.AI20236 cited

Understanding the Capabilities of Large Language Models for Automated Planning

Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan +5

Automated planning is concerned with developing efficient algorithms to generate plans or sequences of actions to achieve a specific goal in a given environment. Emerging Large Lan…

cs.AI20233 cited

Fast and Slow Planning

Francesco Fabiano, Vishal Pallagani, Marianna Bergamaschi Ganapini +5

The concept of Artificial Intelligence has gained a lot of attention over the last decade. In particular, AI-based tools have been employed in several scenarios and are, by now, pe…

cs.CV2021

Deep ensembles in bioimage segmentation

Loris Nanni, Daniela Cuza, Alessandra Lumini +2

Semantic segmentation consists in classifying each pixel of an image by assigning it to a specific label chosen from a set of all the available ones. During the last few years, a l…