3 citations · 9 across the 15 of their papers we have counts for
16 papers
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1
With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…
Robotic Policy Adaptation via Weight-Space Meta-Learning
Christian Bianchi, Siamak Yousefi, Alessio Sampieri +4
Vision-Language-Action (VLA) models are emerging as a promising paradigm for robotic manipulation, enabling general-purpose policies trained from large corpora of demonstrations an…
Not All Latent Spaces Are Flat: Hyperbolic Concept Control
Maria Rosaria Briglia, Simone Facchiano, Paolo Cursi +6
As modern text-to-image (T2I) models draw closer to synthesizing highly realistic content, the threat of unsafe content generation grows, and it becomes paramount to exercise contr…
CaTS-Bench: Can Language Models Describe Time Series?
Luca Zhou, Pratham Yashwante, Marshall Fisher +4
Time series captioning, the task of describing time series in natural language, requires numeric and temporal reasoning, trend interpretation, and contextual understanding. Existin…
Video Unlearning via Low-Rank Refusal Vector
Simone Facchiano, Stefano Saravalle, Matteo Migliarini +7
Video generative models achieve high-quality synthesis from natural-language prompts by leveraging large-scale web data. However, this training paradigm inherently exposes them to…
LongCodeBench: Evaluating Coding LLMs at 1M Context Windows
Stefano Rando, Luca Romani, Alessio Sampieri +5
Context lengths for models have grown rapidly, from thousands to millions of tokens in just a few years. The extreme context sizes of modern long-context models have made it diffic…
Human Motion Unlearning
Edoardo De Matteis, Matteo Migliarini, Alessio Sampieri +2
We introduce Human Motion Unlearning and motivate it through the concrete task of preventing violent 3D motion synthesis, an important safety requirement given that popular text-to…
Social EgoMesh Estimation
Luca Scofano, Alessio Sampieri, Edoardo De Matteis +2
Accurately estimating the 3D pose of the camera wearer in egocentric video sequences is crucial to modeling human behavior in virtual and augmented reality applications. The task p…
Length-Aware Motion Synthesis via Latent Diffusion
Alessio Sampieri, Alessio Palma, Indro Spinelli +1
The target duration of a synthesized human motion is a critical attribute that requires modeling control over the motion dynamics and style. Speeding up an action performance is no…
Following the Human Thread in Social Navigation
Luca Scofano, Alessio Sampieri, Tommaso Campari +4
The success of collaboration between humans and robots in shared environments relies on the robot's real-time adaptation to human motion. Specifically, in Social Navigation, the ag…
Staged Contact-Aware Global Human Motion Forecasting
Luca Scofano, Alessio Sampieri, Elisabeth Schiele +3
Scene-aware global human motion forecasting is critical for manifold applications, including virtual reality, robotics, and sports. The task combines human trajectory and pose fore…
Best Practices for 2-Body Pose Forecasting
Muhammad Rameez Ur Rahman, Luca Scofano, Edoardo De Matteis +3
The task of collaborative human pose forecasting stands for predicting the future poses of multiple interacting people, given those in previous frames. Predicting two people in int…
About latent roles in forecasting players in team sports
Luca Scofano, Alessio Sampieri, Giuseppe Re +3
Forecasting players in sports has grown in popularity due to the potential for a tactical advantage and the applicability of such research to multi-agent interaction systems. Team…
Contracting Skeletal Kinematics for Human-Related Video Anomaly Detection
Alessandro Flaborea, Guido D'Amely, Stefano D'Arrigo +3
Detecting the anomaly of human behavior is paramount to timely recognizing endangering situations, such as street fights or elderly falls. However, anomaly detection is complex sin…
Pose Forecasting in Industrial Human-Robot Collaboration
Alessio Sampieri, Guido D'Amely, Andrea Avogaro +5
Pushing back the frontiers of collaborative robots in industrial environments, we propose a new Separable-Sparse Graph Convolutional Network (SeS-GCN) for pose forecasting. For the…
Space-Time-Separable Graph Convolutional Network for Pose Forecasting
Theodoros Sofianos, Alessio Sampieri, Luca Franco +1
Human pose forecasting is a complex structured-data sequence-modelling task, which has received increasing attention, also due to numerous potential applications. Research has main…