1 citations · 1 across the 7 of their papers we have counts for
7 papers
Assessing VLM-Driven Semantic-Affordance Inference for Non-Humanoid Robot Morphologies
Jess Jones, Raul Santos-Rodriguez, Sabine Hauert
Vision-language models (VLMs) have demonstrated remarkable capabilities in understanding human-object interactions, but their application to robotic systems with non-humanoid morph…
HiPP-Prune: Hierarchical Preference-Conditioned Structured Pruning for Vision-Language Models
Lincen Bai, Hedi Tabia, Raul Santos-Rodriguez
Pruning vision-language models (VLMs) for efficient deployment is challenging because compression can affect not only task utility but also visual grounding, often amplifying objec…
LEMON: Local Explanations via Modality-aware OptimizatioN
Yu Qin, Phillip Sloan, Raul Santos-Rodriguez +2
Multimodal models are ubiquitous, yet existing explainability methods are often single-modal, architecture-dependent, or too computationally expensive to run at scale. We introduce…
TACTFL: Temporal Contrastive Training for Multi-modal Federated Learning with Similarity-guided Model Aggregation
Guanxiong Sun, Majid Mirmehdi, Zahraa Abdallah +3
Real-world federated learning faces two key challenges: limited access to labelled data and the presence of heterogeneous multi-modal inputs. This paper proposes TACTFL, a unified…
LL-VQ-VAE: Learnable Lattice Vector-Quantization For Efficient Representations
Ahmed Khalil, Robert Piechocki, Raul Santos-Rodriguez
In this paper we introduce learnable lattice vector quantization and demonstrate its effectiveness for learning discrete representations. Our method, termed LL-VQ-VAE, replaces the…
Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach
Jonas Schulz, Rafael Poyiadzi, Raul Santos-Rodriguez
Explainability of black-box machine learning models is crucial, in particular when deployed in critical applications such as medicine or autonomous cars. Existing approaches produc…
OPERAnet: A Multimodal Activity Recognition Dataset Acquired from Radio Frequency and Vision-based Sensors
Mohammud J. Bocus, Wenda Li, Shelly Vishwakarma +8
This paper presents a comprehensive dataset intended to evaluate passive Human Activity Recognition (HAR) and localization techniques with measurements obtained from synchronized R…