activity
20232026
most citedSocially Pertinent Robots in Gerontological Healthcare

2 citations · 4 across the 9 of their papers we have counts for

collaborators

10 papers

cs.IR2026

H2CE: Modeling Geo-Semantic Interactions for POI Reranking with Heterogeneous Two-Stage Cross-Encoders

Zhengwei Bai, Moreno D'Incà, Danielle Class +1

Point-of-Interest (POI) reranking in local search must model query-conditioned tradeoffs among lexical semantics, geospatial proximity, and numerical quality signals such as rating…

cs.CV2026

ContextBias: Controlled Evaluation of Bias Persistence Under Context Shift in Text-to-Image Models

Shaghayegh Kolli, Sina Emami, Moreno D'Incà +4

Text-to-image models learn associations between concepts - in the case of this paper, people's professions, which we refer to as roles - and visual attributes. These associations c…

cs.AI2026

Harnessing Textual Refusal Directions for Multimodal Safety

Moreno D'Incà, Nicu Sebe, Massimiliano Mancini

Safety in Multimodal Large Language Models (MLLMs) depends on unsafe multimodal data for post-training alignment or activation steering. However, such data is hard to collect, must…

cs.CV2025

Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers

Quentin Guimard, Moreno D'Incà, Massimiliano Mancini +1

A person downloading a pre-trained model from the web should be aware of its biases. Existing approaches for bias identification rely on datasets containing labels for the task of…

cs.CY2025

Beauty and the Bias: Exploring the Impact of Attractiveness on Multimodal Large Language Models

Aditya Gulati, Moreno D'Incà, Nicu Sebe +2

Physical attractiveness matters. It has been shown to influence human perception and decision-making, often leading to biased judgments that favor those deemed attractive in what i…

cs.CV2025

Safe Vision-Language Models via Unsafe Weights Manipulation

Moreno D'Incà, Elia Peruzzo, Xingqian Xu +3

Vision-language models (VLMs) often inherit the biases and unsafe associations present within their large-scale training dataset. While recent approaches mitigate unsafe behaviors,…

cs.CV2024★ 1 cited

GradBias: Unveiling Word Influence on Bias in Text-to-Image Generative Models

Moreno D'Incà, Elia Peruzzo, Massimiliano Mancini +3

Recent progress in Text-to-Image (T2I) generative models has enabled high-quality image generation. As performance and accessibility increase, these models are gaining significant…

cs.CV2024

OpenBias: Open-set Bias Detection in Text-to-Image Generative Models

Moreno D'Incà, Elia Peruzzo, Massimiliano Mancini +6

Text-to-image generative models are becoming increasingly popular and accessible to the general public. As these models see large-scale deployments, it is necessary to deeply inves…

cs.RO2024★ 2 cited

Socially Pertinent Robots in Gerontological Healthcare

Xavier Alameda-Pineda, Angus Addlesee, Daniel Hernández García +41

Despite the many recent achievements in developing and deploying social robotics, there are still many underexplored environments and applications for which systematic evaluation o…

cs.CV2023★ 1 cited

Improving Fairness using Vision-Language Driven Image Augmentation

Moreno D'Incà, Christos Tzelepis, Ioannis Patras +1

Fairness is crucial when training a deep-learning discriminative model, especially in the facial domain. Models tend to correlate specific characteristics (such as age and skin col…