research
∙
07/24/2023
Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations: an Empirical Study
Sequential Recommender Systems (SRSs) have been widely used to model use...
share
research
∙
07/24/2023
RRAML: Reinforced Retrieval Augmented Machine Learning
The emergence of large language models (LLMs) has revolutionized machine...
research
∙
06/26/2023
Fauno: The Italian Large Language Model that will leave you senza parole!
This paper presents Fauno, the first and largest open-source Italian con...
research
∙
06/01/2023
Renormalized Graph Neural Networks
Graph Neural Networks (GNNs) have become essential for studying complex ...
research
∙
05/18/2023
Integrating Item Relevance in Training Loss for Sequential Recommender Systems
Sequential Recommender Systems (SRSs) are a popular type of recommender ...
research
∙
05/02/2023
Multimodal Neural Databases
The rise in loosely-structured data available through text, images, and ...
research
∙
04/07/2023
Sheaf Neural Networks for Graph-based Recommender Systems
Recent progress in Graph Neural Networks has resulted in wide adoption b...
research
∙
03/16/2023
Combining Distance to Class Centroids and Outlier Discounting for Improved Learning with Noisy Labels
In this paper, we propose a new approach for addressing the challenge of...
research
∙
03/15/2023
Attention-likelihood relationship in transformers
We analyze how large language models (LLMs) represent out-of-context wor...
research
∙
09/20/2022
Sparse Vicious Attacks on Graph Neural Networks
Graph Neural Networks (GNNs) have proven to be successful in several pre...
research
∙
07/27/2022
Encoding Concepts in Graph Neural Networks
The opaque reasoning of Graph Neural Networks induces a lack of human tr...
research
∙
10/22/2021
ReLACE: Reinforcement Learning Agent for Counterfactual Explanations of Arbitrary Predictive Models
The demand for explainable machine learning (ML) models has been growing...
research
∙
10/05/2021
NEWRON: A New Generalization of the Artificial Neuron to Enhance the Interpretability of Neural Networks
In this work, we formulate NEWRON: a generalization of the McCulloch-Pit...
research
∙
06/02/2021
Database Reasoning Over Text
Neural models have shown impressive performance gains in answering queri...
research
∙
04/25/2021
SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images
We describe SemEval-2021 task 6 on Detection of Persuasion Techniques in...
research
∙
04/01/2021
CycleDRUMS: Automatic Drum Arrangement For Bass Lines Using CycleGAN
The two main research threads in computer-based music generation are: th...
research
∙
03/13/2021
A Survey on Multimodal Disinformation Detection
Recent years have witnessed the proliferation of fake news, propaganda, ...
research
∙
02/05/2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
Graph neural networks (GNNs) have shown increasing promise in real-world...
research
∙
10/14/2020
Neural Databases
In recent years, neural networks have shown impressive performance gains...
research
∙
09/22/2020
Preserving Integrity in Online Social Networks
Online social networks provide a platform for sharing information and fr...
research
∙
06/01/2020
Concept Matching for Low-Resource Classification
We propose a model to tackle classification tasks in the presence of ver...
research
∙
01/17/2020
Node Masking: Making Graph Neural Networks Generalize and Scale Better
Graph Neural Networks (GNNs) have received a lot of interest in the rece...
research
∙
11/09/2019
How Decoding Strategies Affect the Verifiability of Generated Text
Language models are of considerable importance. They are used for pretra...
research
∙
05/23/2019
Misspelling Oblivious Word Embeddings
In this paper we present a method to learn word embeddings that are resi...
research
∙
06/20/2017
Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking
Machine-learned models are often described as "black boxes". In many rea...
research
∙
07/07/2016