502 citations · 527 across the 8 of their papers we have counts for
9 papers
Can we trust LLM Self-Explanations for Entity Resolution?
Tommaso Teofili, Donatella Firmani, Nick Koudas +2
Large Language Models (LLMs) have recently shown strong performance on Entity Resolution (ER). Additionally, akin to their prowess in providing accurate predictions, these models o…
Towards Realistic Synthetic Data for Automatic Drum Transcription
Pierfrancesco Melucci, Paolo Merialdo, Taketo Akama
Deep learning models define the state-of-the-art in Automatic Drum Transcription (ADT), yet their performance is contingent upon large-scale, paired audio-MIDI datasets, which are…
How to Connect Speech Foundation Models and Large Language Models? What Matters and What Does Not
Francesco Verdini, Pierfrancesco Melucci, Stefano Perna +9
The remarkable performance achieved by Large Language Models (LLM) has driven research efforts to leverage them for a wide range of tasks and input modalities. In speech-to-text (S…
Effective Explanations for Entity Resolution Models
Tommaso Teofili, Donatella Firmani, Nick Koudas +3
Entity resolution (ER) aims at matching records that refer to the same real-world entity. Although widely studied for the last 50 years, ER still represents a challenging data mana…
Alaska: A Flexible Benchmark for Data Integration Tasks
Valter Crescenzi, Andrea De Angelis, Donatella Firmani +4
Data integration is a long-standing interest of the data management community and has many disparate applications, including business, science and government. We have recently witn…
Knowledge Graph Embedding for Link Prediction: A Comparative Analysis
Andrea Rossi, Donatella Firmani, Antonio Matinata +2
Knowledge Graphs (KGs) have found many applications in industry and academic settings, which in turn, have motivated considerable research efforts towards large-scale information e…
Multikernel activation functions: formulation and a case study
Simone Scardapane, Elena Nieddu, Donatella Firmani +1
The design of activation functions is a growing research area in the field of neural networks. In particular, instead of using fixed point-wise functions (e.g., the rectified linea…
Towards Knowledge Discovery from the Vatican Secret Archives. In Codice Ratio -- Episode 1: Machine Transcription of the Manuscripts
Donatella Firmani, Marco Maiorino, Paolo Merialdo +1
In Codice Ratio is a research project to study tools and techniques for analyzing the contents of historical documents conserved in the Vatican Secret Archives (VSA). In this paper…
Web Content Extraction - a Meta-Analysis of its Past and Thoughts on its Future
Tim Weninger, Rodrigo Palacios, Valter Crescenzi +2
In this paper, we present a meta-analysis of several Web content extraction algorithms, and make recommendations for the future of content extraction on the Web. First, we find tha…