In recent years, the integration of large language models (LLMs) has revolutionized the field
of robotics, enabling robots to communicate, understand, and reason with human-like …

3D visual grounding is a critical skill for household robots, enabling them to navigate,
manipulate objects, and answer questions based on their environment. While existing …

Large vision language models (LVLMs) often suffer from object hallucination, producing
objects not present in the given images. While current benchmarks for object hallucination …

Abstract We introduce One-shot Open Affordance Learning (OOAL) where a model is trained
with just one example per base object category but is expected to identify novel objects and …

LLMs with visual inputs, ie, Vision Language Models (VLMs), have the capacity to process
state information as visual-textual prompts and respond with policy decisions in text. We …

Affordance, defined as the potential actions that an object offers, is crucial for robotic
manipulation tasks. A deep understanding of affordance can lead to more intelligent AI …

The integration of Multimodal Large Language Models (MLLMs) with robotic systems has
significantly enhanced the ability of robots to interpret and act upon natural language …

Humans show an innate capability to identify tools to support specific actions. The
association between objects parts and the actions they facilitate is usually named …

Vision Transformers (ViTs) have emerged as the backbone of many segmentation models,
consistently achieving state-of-the-art (SOTA) performance. However, their success comes …

Egocentric Hand Object Interaction (HOI) videos provide valuable insights into human
interactions with the physical world, attracting growing interest from the computer vision and …