2 citations · 3 across the 16 of their papers we have counts for
19 papers
Prompted Identity Degrades Cooperation in Multi-Agent LLM Systems
Xavier Del Giudice, Alessio Palma, Matteo Migliarini +2
Multi-agent LLM systems increasingly mix models from several providers, yet exposing each agent's underlying model identity to its peers significantly impairs cooperation. We show…
Robots Ask the Way: Communication-Enabled Social Navigation
Valentino Sacco, Luca Scofano, Indro Spinelli +1
Assistive autonomous robots operating in multi-agent environments require efficient strategies to locate specific individuals among multiple residents. Current social navigation me…
T-Rex: Tactile-Reactive Dexterous Manipulation
Dantong Niu, Zhuoyang Liu, Zekai Wang +31
The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based Vision-Language-Action (VLA) mo…
Contrastive Action-Image Pre-training for Visuomotor Control
Yuvan Sharma, Dantong Niu, Anirudh Pai +16
Existing vision encoders for robotics face a fundamental bottleneck: robotic datasets lack the scale necessary for large-scale pre-training. Prior work circumvents this data scarci…
Bimanual Robot Manipulation via Multi-Agent In-Context Learning
Alessio Palma, Indro Spinelli, Vignesh Prasad +4
Large Language Models (LLMs) have emerged as powerful reasoning engines for embodied control. In particular, In-Context Learning (ICL) enables off-the-shelf, text-only LLMs to pred…
Describe-Then-Act: Proactive Agent Steering via Distilled Language-Action World Models
Massimiliano Pappa, Luca Romani, Valentino Sacco +5
Deploying safety-critical agents requires anticipating the consequences of actions before they are executed. While world models offer a paradigm for this proactive foresight, curre…
PhysTalk: Language-driven Real-time Physics in 3D Gaussian Scenes
Luca Collorone, Mert Kiray, Indro Spinelli +2
Realistic visual simulations are omnipresent, yet their creation requires computing time, rendering, and expert animation knowledge. Open-vocabulary visual effects generation from…
MonSTeR: a Unified Model for Motion, Scene, Text Retrieval
Luca Collorone, Matteo Gioia, Massimiliano Pappa +5
Intention drives human movement in complex environments, but such movement can only happen if the surrounding context supports it. Despite the intuitive nature of this mechanism, e…
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…
ANTHROPOS-V: benchmarking the novel task of Crowd Volume Estimation
Luca Collorone, Stefano D'Arrigo, Massimiliano Pappa +3
We introduce the novel task of Crowd Volume Estimation (CVE), defined as the process of estimating the collective body volume of crowds using only RGB images. Besides event managem…
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…
TI-PREGO: Chain of Thought and In-Context Learning for Online Mistake Detection in PRocedural EGOcentric Videos
Leonardo Plini, Luca Scofano, Edoardo De Matteis +6
Identifying procedural errors online from egocentric videos is a critical yet challenging task across various domains, including manufacturing, healthcare, and skill-based training…
Compositional Entailment Learning for Hyperbolic Vision-Language Models
Avik Pal, Max van Spengler, Guido Maria D'Amely di Melendugno +3
Image-text representation learning forms a cornerstone in vision-language models, where pairs of images and textual descriptions are contrastively aligned in a shared embedding spa…
OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based Cameras
Muhammad Rameez Ur Rahman, Jhony H. Giraldo, Indro Spinelli +2
Event cameras, known for low-latency operation and superior performance in challenging lighting conditions, are suitable for sensitive computer vision tasks such as semantic segmen…
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…
Hyp2Nav: Hyperbolic Planning and Curiosity for Crowd Navigation
Guido Maria D'Amely di Melendugno, Alessandro Flaborea, Pascal Mettes +1
Autonomous robots are increasingly becoming a strong fixture in social environments. Effective crowd navigation requires not only safe yet fast planning, but should also enable int…
PREGO: online mistake detection in PRocedural EGOcentric videos
Alessandro Flaborea, Guido Maria D'Amely di Melendugno, Leonardo Plini +5
Promptly identifying procedural errors from egocentric videos in an online setting is highly challenging and valuable for detecting mistakes as soon as they happen. This capability…
MoDiPO: text-to-motion alignment via AI-feedback-driven Direct Preference Optimization
Massimiliano Pappa, Luca Collorone, Giovanni Ficarra +2
Diffusion Models have revolutionized the field of human motion generation by offering exceptional generation quality and fine-grained controllability through natural language condi…
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…