Suggestions and research areas for thesis and project activities
Neural-Symbolic techniques aim to combine the efficiency and effectiveness of neural architectures with the advantages of symbolic or relational techniques in terms of use of prior knowledge, explainability, compliance, and interpretability.
Despite the existence of many NeSy frameworks, few of them are suited to be applied in the NLP domain, for various reasons.
We are interested in extending such frameworks to NLP tasks, and in applying them to challenging problems, such as Argument Mining.
Possible thesis/projects:
Modern machine learning techniques have proven capable of learning even very abstract and high-level concepts, but usually with a caveat: they need plenty of data! Even those techniques that allow unsupervised or semi-supervised learning, still need accurate and reliable ground truth to validate and test the final models.
For these reasons, the development of corpora and datasets is a fundamental step towards the development of new models and techniques that can address complex tasks.
We are interested in creating and testing new language resources, especially for tasks that require expert knowledge/skills and/or languages other than English.
We are also interested in using these resources to develop and/or test new models and techniques.
Possible thesis/projects:
The domain of legal documents is one of those that would benefit the most from a wide development and application of NLP tools. At the same time, it typically requires a human a high level of specialization and background knowledge to perform tasks in this context, which are difficult to transfer to an automatic tool.
In this context, we are involved in multiple projects (see ADELE and LAILA on the Projects page), which address tasks such as: argument mining, summarization, outcome prediction, cross-lingual transfer of knowledge.
Our purpose is to research and develop tools that can have a meaningful impact on the community.
We are in close contact with teams of experts that can provide their expertise and we have access to reserved datasets that can be used to develop automatic tools.
Possible thesis/projects:
Dialogue Systems are a pervasive technology that is getting more and more popular in every aspect of our life.
We are especially interested in analysing aspects that are usually not addressed by mainstream companies.
Possible projects/thesis are:
One of our main research interests is Argument/Argumentation Mining (AM). It can be informally described as the problem of automatically detecting and extracting arguments from the text. Arguments are usually represented as a combination of a premise (a fact) that supports a subjective conclusion (opinion, claim).
Argumentation Mining touches a wide variety of well-known NLP tasks, spanning from sentiment analysis, stance detection to summarization and dialogue systems.
Possible projects/thesis are:
We are interested in developing deep learning models that are capable of employing knowledge in the form of natural language. Such knowledge is easy to interpret and to define (compared to structured representations like syntactic trees, knowledge graphs and symbolic rules). Unstructured knowledge increases the interpretability of models and goes in the direction of defining a realistic type of artificial intelligence. However, properly integrating this type of information is particularly challenging due to its inherent ambiguity and variability.