My Publications
2020
- “Explainable Inference on Sequential Data via Memory-Tracking”.
Biagio La Rosa, Roberto Capobianco and Daniele Nardi.
In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20)
[BibTeX] [PDF] [Code] [Blog Post].
@inproceedings{LaRosa20, title = {Explainable Inference on Sequential Data via Memory-Tracking}, author = {La Rosa, Biagio and Capobianco, Roberto and Nardi, Daniele}, booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, {IJCAI-20}}, publisher = {International Joint Conferences on Artificial Intelligence Organization}, pages = {2006--2013}, year = {2020}, month = {7}, doi = {10.24963/ijcai.2020/278}, url = {https://doi.org/10.24963/ijcai.2020/278}, }
Theses
Master
Short Abstract: The thesis presents a novel mechanism to get hints of
explanation exploiting the capability of
memory-based networks – Differential Neural Computers – to store data in memory and reusing it
for inference. By tracking both the memory access at prediction
time, and the information stored by the network at each step of
the input sequence, it is possible to retrieve the most relevant input steps associated to each prediction. The mechanism is tested on two problems: a modified version of T-Maze and the Story Cloze Test task. The work studies also the influence of parameters and the adequacy of the extracted explanations.
Area: Explainable Artificial Intelligence
Supervisor: Roberto Capobianco
Bachelor
Short Abstract: The work presents a supersense tagger based on Wikipedia and BabelNet.
SuperSense tagging is a Natural Language Processing task that consists in annotating each
entity in a text according to a general semantic taxonomy. In our case BabelNet is used as
taxonomy, extracting the most used words and collecting the nouns that can indicate a category.
Exploiting the is-a relations of BabelNet, then Wikipedia is annotated with the extracted concepts
and used as dataset for the training of an SVM classifier based on the framework It Makes Sense.
Area: Natural Language Processing
Supervisor: Roberto Navigli