5 citations · 10 across the 5 of their papers we have counts for
6 papers
LLMs as Data Annotators: How Close Are We to Human Performance
Muhammad Uzair Ul Haq, Davide Rigoni, Alessandro Sperduti
In NLP, fine-tuning LLMs is effective for various applications but requires high-quality annotated data. However, manual annotation of data is labor-intensive, time-consuming, and…
RGCVAE: Relational Graph Conditioned Variational Autoencoder for Molecule Design
Davide Rigoni, Nicolò Navarin, Alessandro Sperduti
Identifying molecules that exhibit some pre-specified properties is a difficult problem to solve. In the last few years, deep generative models have been used for molecule generati…
Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement
Davide Rigoni, Luca Parolari, Luciano Serafini +2
Using only image-sentence pairs, weakly-supervised visual-textual grounding aims to learn region-phrase correspondences of the respective entity mentions. Compared to the supervise…
A Better Loss for Visual-Textual Grounding
Davide Rigoni, Luciano Serafini, Alessandro Sperduti
Given a textual phrase and an image, the visual grounding problem is the task of locating the content of the image referenced by the sentence. It is a challenging task that has sev…
Conditional Constrained Graph Variational Autoencoders for Molecule Design
Davide Rigoni, Nicolò Navarin, Alessandro Sperduti
In recent years, deep generative models for graphs have been used to generate new molecules. These models have produced good results, leading to several proposals in the literature…
A Systematic Assessment of Deep Learning Models for Molecule Generation
Davide Rigoni, Nicolò Navarin, Alessandro Sperduti
In recent years the scientific community has devoted much effort in the development of deep learning models for the generation of new molecules with desirable properties (i.e. drug…