Tootfinder

Documenting Deployment with Fabric: A Repository of Real-World AI Governance
Mackenzie Jorgensen, Kendall Brogle, Katherine M. Collins, Lujain Ibrahim, Arina Shah, Petra Ivanovic, Noah Broestl, Gabriel Piles, Paul Dongha, Hatim Abdulhussein, Adrian Weller, Jillian Powers, Umang Bhatt
https://arxiv.org/abs/2508.14119

Documenting Deployment with Fabric: A Repository of Real-World AI Governance
Artificial intelligence (AI) is increasingly integrated into society, from financial services and traffic management to creative writing. Academic literature on the deployment of AI has mostly focused on the risks and harms that result from the use of AI. We introduce Fabric, a publicly available repository of deployed AI use cases to outline their governance mechanisms. Through semi-structured interviews with practitioners, we collect an initial set of 20 AI use cases. In addition, we co-desig…

Role, cost, and complexity of software in the real-world: a case for formal methods
Giovanni Bernardi, Adrian Francalanza, Marco Peressotti, Mohammad Reza Mousavi
https://arxiv.org/abs/2506.13821

Role, cost, and complexity of software in the real-world: a case for formal methods
In this chapter we outline the role that software has in modern society, along with the staggering costs of poor software quality. To lay this bare, we recall the costs of some of the major software failures that happened during the last~$40$ years. We argue that these costs justify researching, studying and applying formal software verification and in particular program analysis. This position is supported by successful industrial experiences.

Bias and Identifiability in the Bounded Confidence Model
Claudio Borile, Jacopo Lenti, Valentina Ghidini, Corrado Monti, Gianmarco De Francisci Morales
https://arxiv.org/abs/2506.11751

Bias and Identifiability in the Bounded Confidence Model
Opinion dynamics models such as the bounded confidence models (BCMs) describe how a population can reach consensus, fragmentation, or polarization, depending on a few parameters. Connecting such models to real-world data could help understanding such phenomena, testing model assumptions. To this end, estimation of model parameters is a key aspect, and maximum likelihood estimation provides a principled way to tackle it. Here, our goal is to outline the properties of statistical estimators of th…