Languages are known to describe the world in diverse ways. Across lexico...
Recent work in Machine Learning and Computer Vision has highlighted the
...
It is well known that AI-based language technology – large language mode...
It is a well-known fact that current AI-based language technology – lang...
One population group that had to significantly adapt and change their
be...
This study analyzes the possible relationship between personality traits...
When building a new application we are increasingly confronted with the ...
We are interested in aligning how people think about objects and what
ma...
Data quality is critical for multimedia tasks, while various types of
sy...
The mainstream approach to the development of ontologies is merging
onto...
The main goal of this paper is to evaluate knowledge base schemas, model...
Smartphones enable understanding human behavior with activity recognitio...
We discuss two kinds of semantics relevant to Computer Vision (CV) syste...
Mood inference with mobile sensing data has been studied in ubicomp
lite...
More and more, with the growing focus on large scale analytics, we are
c...
One of the major barriers to the training of algorithms on knowledge gra...
Semantic Heterogeneity is conventionally understood as the existence of
...
We propose a model of the situational context of a person and show how i...
The SIGMORPHON 2022 shared task on morpheme segmentation challenged syst...
Part-prototype Networks (ProtoPNets) are concept-based classifiers desig...
The Universal Morphology (UniMorph) project is a collaborative effort
pr...
This paper describes a method to enrich lexical resources with content
r...
The Universal Knowledge Core (UKC) is a large multilingual lexical datab...
Diversity-aware platform design is a paradigm that responds to the ethic...
Recent work in Machine Learning and Computer Vision has provided evidenc...
We base our work on the teleosemantic modelling of concepts as abilities...
We are concerned with debugging concept-based gray-box models (GBMs). Th...
We are interested in dealing with the heterogeneity of Knowledge bases (...
The representation of the personal context is complex and essential to
i...
We tackle sequential learning under label noise in applications where a ...
We propose a novel approach to the problem of semantic heterogeneity whe...
We assume that substances in the world are represented by two types of
c...
It is a fact that, when developing a new application, it is virtually
im...
In Visual Semantics we study how humans build mental representations, i....
As the role of algorithmic systems and processes increases in society, s...
The complexity and non-Euclidean structure of graph data hinder the
deve...
Mitigating bias in algorithmic systems is a critical issue drawing atten...
We introduce and study knowledge drift (KD), a complex form of drift tha...
Applications like personal assistants need to be aware ofthe user's cont...
The ability to learn from human supervision is fundamental for personal
...
Among the general population, students are especially sensitive to socia...
We are interested in the problem of continual object recognition in a se...
Large-scale knowledge bases have currently reached impressive sizes; how...