Search
Now showing items 1-10 of 16
Logical properties of Natural Language Inference - Experiments with Synthetic Data to Study Consequence Relations in LSTMs
(2024-06-17)
Natural language inference (NLI) datasets are great resources to train and benchmark
models that infer entailment relations. However, these datasets are known to have issues
such as lexical biases that affect the behaviour ...
Automatic Idiomatic Expression Detection. Comparison Between GPT-4 and Gemini Pro Prompt Engineering & LSTM-RNN Construction
(2024-06-18)
This thesis explores the concept of detecting non-literal phrases using Large Language
Models (LLM) such as GPT-4 and Gemini Pro, as well as Recurrent Neural Networks
(RNN), LSTM and BiLSTM models in particular.
Through ...
Evaluating the contribution of framenet to gender-based violence identification - How semantic annotation can be used as a resource for identifying patterns of violence
(2024-06-17)
According to the World Health Organization, one in three women has been a victim of physical or sexual
violence by their partner at some point in their lives. This indicates that Gender-Based Violence is a global
public ...
Don't Mention the Norm
(2024-06-17)
Reporting bias (the human tendency to not mention obvious or redundant information)
and social bias (societal attitudes toward specific demographic groups) have both
been shown to propagate from human text data to language ...
PERSONALIZED LANGUAGE LEARNING IN THE AGE OF AI. Leveraging Large Language Models for Optimal Learning Outcomes.
(2024-06-25)
In a new era marked by technological advancements and the AI boom, language learning is no
longer limited to the classrooms. The emergence of Large Language Models (LLMs) propels
further advancements within language ...
Creating Synthetic Dialogue Datasets for NLU Training. An Approach Using Large Language Models
(2024-06-20)
This thesis explores the topic of using the GPT-4 large language model, to generate high-quality,
diverse synthetic dialogue datasets for training Natural Language Understanding (NLU) models
in task-oriented dialogue ...
MACHINE TRANSLATION FROM ANCIENT GREEK TO ENGLISH: EXPERIMENTS WITH OPENNMT
(2024-06-17)
The current thesis focuses on the application of neural machine translation (NMT) models translating from
Ancient Greek to English. The rich morphology, syntax, and vocabulary of the Ancient Greek combined
with its status ...
EXPLORING LEXICAL SEMANTIC CHANGE IN POLISH USING XL-LEXEME
(2024-06-17)
The scope of this thesis is on Lexical Semantic Change (LSC) and its automatic detection in the Polish language.
Following Cassotti et al. (2023)’s findings, the following thesis leverages XL-Lexeme, a transformerbased
...
Fine-Tuning Large Language Models for Practical Software Engineering: Case Studies in Automated Patch Generation
(2024-10-21)
In recent years, software development has become increasingly complex, posing challenges in problem-solving, code optimization, and error correction. The rise of Artificial Intelligence (AI) and Large Language Models (LLMs) ...
IMPLEMENTING A GROUNDING MODULE FOR AN NPC Testing grounding of novel names with state charts and LLMs
(2024-11-12)
In this work we argue that any system that processes spoken human language should incorporate
mechanisms for grounding, as it is an essential part of human communication. Because of this, we
explore two name-grounding ...