2 citations · 10 across the 9 of their papers we have counts for
11 papers
Lifelong Robot Library Learning: Bootstrapping Composable and Generalizable Skills for Embodied Control with Language Models
Georgios Tziafas, Hamidreza Kasaei
Large Language Models (LLMs) have emerged as a new paradigm for embodied reasoning and control, most recently by generating robot policy code that utilizes a custom library of visi…
3D Feature Distillation with Object-Centric Priors
Georgios Tziafas, Yucheng Xu, Zhibin Li +1
Grounding natural language to the physical world is a ubiquitous topic with a wide range of applications in computer vision and robotics. Recently, 2D vision-language models such a…
Towards Open-World Grasping with Large Vision-Language Models
Georgios Tziafas, Hamidreza Kasaei
The ability to grasp objects in-the-wild from open-ended language instructions constitutes a fundamental challenge in robotics. An open-world grasping system should be able to comb…
Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter
Georgios Tziafas, Yucheng Xu, Arushi Goel +3
Robots operating in human-centric environments require the integration of visual grounding and grasping capabilities to effectively manipulate objects based on user instructions. T…
Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models
Songsong Xiong, Georgios Tziafas, Hamidreza Kasaei
Robots operating in human-centered environments, such as retail stores, restaurants, and households, are often required to distinguish between similar objects in different contexts…
Enhancing Interpretability and Interactivity in Robot Manipulation: A Neurosymbolic Approach
Georgios Tziafas, Hamidreza Kasaei
In this paper we present a neurosymbolic architecture for coupling language-guided visual reasoning with robot manipulation. A non-expert human user can prompt the robot using unco…
Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition
Georgios Tziafas, Hamidreza Kasaei
The Vision Transformer (ViT) architecture has established its place in computer vision literature, however, training ViTs for RGB-D object recognition remains an understudied topic…
Sim-To-Real Transfer of Visual Grounding for Human-Aided Ambiguity Resolution
Georgios Tziafas, Hamidreza Kasaei
Service robots should be able to interact naturally with non-expert human users, not only to help them in various tasks but also to receive guidance in order to resolve ambiguities…
Improving BERT Pretraining with Syntactic Supervision
Giorgos Tziafas, Konstantinos Kogkalidis, Gijs Wijnholds +1
Bidirectional masked Transformers have become the core theme in the current NLP landscape. Despite their impressive benchmarks, a recurring theme in recent research has been to que…
Fighting the COVID-19 Infodemic with a Holistic BERT Ensemble
Giorgos Tziafas, Konstantinos Kogkalidis, Tommaso Caselli
This paper describes the TOKOFOU system, an ensemble model for misinformation detection tasks based on six different transformer-based pre-trained encoders, implemented in the cont…
Few-Shot Visual Grounding for Natural Human-Robot Interaction
Giorgos Tziafas, Hamidreza Kasaei
Natural Human-Robot Interaction (HRI) is one of the key components for service robots to be able to work in human-centric environments. In such dynamic environments, the robot need…