122 citations · 266 across the 21 of their papers we have counts for
27 papers
Multimodal Neural Databases
Giovanni Trappolini, Andrea Santilli, Emanuele Rodolà +2
The rise in loosely-structured data available through text, images, and other modalities has called for new ways of querying them. Multimedia Information Retrieval has filled this…
Sheaf4Rec: Sheaf Neural Networks for Graph-based Recommender Systems
Antonio Purificato, Giulia Cassarà, Federico Siciliano +2
Recent advancements in Graph Neural Networks (GNN) have facilitated their widespread adoption in various applications, including recommendation systems. GNNs have proven to be effe…
Sparse Vicious Attacks on Graph Neural Networks
Giovanni Trappolini, Valentino Maiorca, Silvio Severino +3
Graph Neural Networks (GNNs) have proven to be successful in several predictive modeling tasks for graph-structured data. Amongst those tasks, link prediction is one of the fundame…
Encoding Concepts in Graph Neural Networks
Lucie Charlotte Magister, Pietro Barbiero, Dmitry Kazhdan +5
The opaque reasoning of Graph Neural Networks induces a lack of human trust. Existing graph network explainers attempt to address this issue by providing post-hoc explanations, how…
GREASE: Generate Factual and Counterfactual Explanations for GNN-based Recommendations
Ziheng Chen, Fabrizio Silvestri, Jia Wang +4
Recently, graph neural networks (GNNs) have been widely used to develop successful recommender systems. Although powerful, it is very difficult for a GNN-based recommender system t…
Detecting and Understanding Harmful Memes: A Survey
Shivam Sharma, Firoj Alam, Md. Shad Akhtar +7
The automatic identification of harmful content online is of major concern for social media platforms, policymakers, and society. Researchers have studied textual, visual, and audi…
NEWRON: A New Generalization of the Artificial Neuron to Enhance the Interpretability of Neural Networks
Federico Siciliano, Maria Sofia Bucarelli, Gabriele Tolomei +1
In this work, we formulate NEWRON: a generalization of the McCulloch-Pitts neuron structure. This new framework aims to explore additional desirable properties of artificial neuron…
ReLAX: Reinforcement Learning Agent eXplainer for Arbitrary Predictive Models
Ziheng Chen, Fabrizio Silvestri, Jia Wang +3
Counterfactual examples (CFs) are one of the most popular methods for attaching post-hoc explanations to machine learning (ML) models. However, existing CF generation methods eithe…
Detecting Propaganda Techniques in Memes
Dimitar Dimitrov, Bishr Bin Ali, Shaden Shaar +5
Propaganda can be defined as a form of communication that aims to influence the opinions or the actions of people towards a specific goal; this is achieved by means of well-defined…
Database Reasoning Over Text
James Thorne, Majid Yazdani, Marzieh Saeidi +3
Neural models have shown impressive performance gains in answering queries from natural language text. However, existing works are unable to support database queries, such as "List…
SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images
Dimitar Dimitrov, Bishr Bin Ali, Shaden Shaar +5
We describe SemEval-2021 task 6 on Detection of Persuasion Techniques in Texts and Images: the data, the annotation guidelines, the evaluation setup, the results, and the participa…
CycleDRUMS: Automatic Drum Arrangement For Bass Lines Using CycleGAN
Giorgio Barnabò, Giovanni Trappolini, Lorenzo Lastilla +4
The two main research threads in computer-based music generation are: the construction of autonomous music-making systems, and the design of computer-based environments to assist m…
A Survey on Multimodal Disinformation Detection
Firoj Alam, Stefano Cresci, Tanmoy Chakraborty +6
Recent years have witnessed the proliferation of offensive content online such as fake news, propaganda, misinformation, and disinformation. While initially this was mostly about t…
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
Ana Lucic, Maartje ter Hoeve, Gabriele Tolomei +2
Given the increasing promise of graph neural networks (GNNs) in real-world applications, several methods have been developed for explaining their predictions. Existing methods for…
Neural Databases
James Thorne, Majid Yazdani, Marzieh Saeidi +3
In recent years, neural networks have shown impressive performance gains on long-standing AI problems, and in particular, answering queries from natural language text. These advanc…
Preserving Integrity in Online Social Networks
Alon Halevy, Cristian Canton Ferrer, Hao Ma +5
Online social networks provide a platform for sharing information and free expression. However, these networks are also used for malicious purposes, such as distributing misinforma…
Concept Matching for Low-Resource Classification
Federico Errica, Ludovic Denoyer, Bora Edizel +4
We propose a model to tackle classification tasks in the presence of very little training data. To this aim, we approximate the notion of exact match with a theoretically sound mec…
Node Masking: Making Graph Neural Networks Generalize and Scale Better
Pushkar Mishra, Aleksandra Piktus, Gerard Goossen +1
Graph Neural Networks (GNNs) have received a lot of interest in the recent times. From the early spectral architectures that could only operate on undirected graphs per a transduct…
How Decoding Strategies Affect the Verifiability of Generated Text
Luca Massarelli, Fabio Petroni, Aleksandra Piktus +5
Recent progress in pre-trained language models led to systems that are able to generate text of an increasingly high quality. While several works have investigated the fluency and…
Misspelling Oblivious Word Embeddings
Bora Edizel, Aleksandra Piktus, Piotr Bojanowski +3
In this paper we present a method to learn word embeddings that are resilient to misspellings. Existing word embeddings have limited applicability to malformed texts, which contain…
Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking
Gabriele Tolomei, Fabrizio Silvestri, Andrew Haines +1
Machine-learned models are often described as "black boxes". In many real-world applications however, models may have to sacrifice predictive power in favour of human-interpretabil…
Pornography consumption in Social Media
Mauro Coletto, Luca Maria Aiello, Claudio Lucchese +1
The structure of a social network is fundamentally related to the interests of its members. People assort spontaneously based on the topics that are relevant to them, forming socia…
On the Behaviour of Deviant Communities in Online Social Networks
Mauro Coletto, Luca Maria Aiello, Claudio Lucchese +1
On-line social networks are complex ensembles of inter-linked communities that interact on different topics. Some communities are characterized by what are usually referred to as d…
Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising
Mihajlo Grbovic, Nemanja Djuric, Vladan Radosavljevic +6
Sponsored search represents a major source of revenue for web search engines. This popular advertising model brings a unique possibility for advertisers to target users' immediate…