Air pollution in our cities is a very significant cause of death and worsening of
the quality of life in current times. Knowing in depth this phenomenon and its
details and building tools that help us to mitigate its ...
Lexical collocations may be identified and categorized in context, which is helpful
for language acquisition, dictionary creation, and many other downstream NLP
tasks. However, the automatic collocation extraction and ...
Inverse Optimal Control (IOC) deals with the problem of recovering an unknown
cost function in a Markov decision process from expert demonstrations acting optimally.
In this thesis we apply IOC to SARS-CoV-2 data. For ...
Personalized medicine is a rapidly evolving field to which many resources have been
devoted recently. It represents a paradigm shift from a one-size-fits-all approach
to healthcare, focusing instead on tailoring treatments ...
A subclass of Markov Decision Processes (MDPs), the Linearly solvable Markov
Decision Processes (LMDPs), which have discrete state space and continuous control
space, allow for a significant simplification of the inverse ...
This paper investigates the phenomenon of memorization in large language models (LLMs), focusing on its dynamics throughout the training process and its implications for data privacy and copyright compliance. While LLMs ...
This thesis builds on the Common Sense-Based Open World Planning (COWP)
framework, which integrates a classical task planner with an LLM module to enable
robot autonomy in open world household environments. The framework ...
This paper explores the development of a real-time people tracking system for immersive interactive environments using open-source deep learning models. The goal was to create an AI-based solution capable of tracking people ...
This thesis explores the integration of imitation learning and policy representation within the domain of constrained reinforcement learning (CRL) to enhance decision making in environments with stringent limitations. ...
The use of Large Language Models (LLMs) as general-purpose assistants is getting more widespread every day. Despite this, the deployment of these models in high-risk scenarios remains controversial due to issues such as ...
The rise of online discussion platforms has transformed the way people communicate, exchange ideas, and engage with information. From social media platforms like Reddit, Twitter, and Facebook to specialized forums and ...
This thesis explores the enhancement of PyramidApp, a tool designed to facilitate
Computer-Supported Collaborative Learning (CSCL) activities. The research addresses
the challenges and opportunities presented by digital ...
Retinopathy of Prematurity (ROP) is a severe retinal vascular disorder affecting premature infants, characterized by abnormal vessel proliferation that can lead to vision impairment or blindness if untreated. Timely and ...
This master’s thesis explores recent advancements in machine learning, particularly those enabling the generation of 3D graphics assets from textual descriptions or input images. Central to this research is the evaluation ...
Computer Supported Collaborative Learning (CSCL) supports the learning process by incorporating technologies that emphasize social interactions. A critical component of successful CSCL implementation is social presence, ...