3 citations · 8 across the 11 of their papers we have counts for
13 papers
Following Delegation Traces to Study Human Oversight in Interaction with Multimodal AI
Agnese Chiatti, Matteo Matteucci, Viola Schiaffonati
As multimodal AI systems are becoming our everyday thought partners, the shift towards studying how users transfer control to these systems becomes especially urgent. In this paper…
The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning
Agnese Chiatti, Michael Cochez, Cristina Cornelio +14
Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statistical approaches of neural n…
Trust in Vision-Language Models: Insights from a Participatory User Workshop
Agnese Chiatti, Lara Piccolo, Sara Bernardini +2
With the growing deployment of Vision-Language Models (VLMs), pre-trained on large image-text and video-text datasets, it is critical to equip users with the tools to discern when…
Mapping User Trust in Vision Language Models: Research Landscape, Challenges, and Prospects
Agnese Chiatti, Sara Bernardini, Lara Shibelski Godoy Piccolo +2
The rapid adoption of Vision Language Models (VLMs), pre-trained on large image-text and video-text datasets, calls for protecting and informing users about when to trust these sys…
Mutual Understanding between People and Systems via Neurosymbolic AI and Knowledge Graphs
Irene Celino, Mario Scrocca, Agnese Chiatti
This chapter investigates the concept of mutual understanding between humans and systems, positing that Neuro-symbolic Artificial Intelligence (NeSy AI) methods can significantly e…
Neuro-Symbolic Scene Graph Conditioning for Synthetic Image Dataset Generation
Giacomo Savazzi, Eugenio Lomurno, Cristian Sbrolli +2
As machine learning models increase in scale and complexity, obtaining sufficient training data has become a critical bottleneck due to acquisition costs, privacy constraints, and…
More than the Sum of Its Parts: Ensembling Backbone Networks for Few-Shot Segmentation
Nico Catalano, Alessandro Maranelli, Agnese Chiatti +1
Semantic segmentation is a key prerequisite to robust image understanding for applications in \acrlong{ai} and Robotics. \acrlong{fss}, in particular, concerns the extension and op…
Surgical fine-tuning for Grape Bunch Segmentation under Visual Domain Shifts
Agnese Chiatti, Riccardo Bertoglio, Nico Catalano +2
Mobile robots will play a crucial role in the transition towards sustainable agriculture. To autonomously and effectively monitor the state of plants, robots ought to be equipped w…
Commonsense Spatial Reasoning for Visually Intelligent Agents
Agnese Chiatti, Gianluca Bardaro, Enrico Motta +1
Service robots are expected to reliably make sense of complex, fast-changing environments. From a cognitive standpoint, they need the appropriate reasoning capabilities and backgro…
Fit to Measure: Reasoning about Sizes for Robust Object Recognition
Agnese Chiatti, Enrico Motta, Enrico Daga +1
Service robots can help with many of our daily tasks, especially in those cases where it is inconvenient or unsafe for us to intervene: e.g., under extreme weather conditions or wh…
Towards a Framework for Visual Intelligence in Service Robotics: Epistemic Requirements and Gap Analysis
Agnese Chiatti, Enrico Motta, Enrico Daga
A key capability required by service robots operating in real-world, dynamic environments is that of Visual Intelligence, i.e., the ability to use their vision system, reasoning co…
Guess What's on my Screen? Clustering Smartphone Screenshots with Active Learning
Agnese Chiatti, Dolzodmaa Davaasuren, Nilam Ram +3
A significant proportion of individuals' daily activities is experienced through digital devices. Smartphones in particular have become one of the preferred interfaces for content…
Text Extraction and Retrieval from Smartphone Screenshots: Building a Repository for Life in Media
Agnese Chiatti, Mu Jung Cho, Anupriya Gagneja +7
Daily engagement in life experiences is increasingly interwoven with mobile device use. Screen capture at the scale of seconds is being used in behavioral studies and to implement…