5 citations · 8 across the 18 of their papers we have counts for
18 papers
Overview of BioASQ 2026: The fourteenth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering
Anastasios Nentidis, Georgios Katsimpras, Anastasia Krithara +18
This paper presents an overview of the fourteenth edition of the BioASQ challenge, organized in the context of the Conference and Labs of the Evaluation Forum (CLEF) 2026. BioASQ i…
Efficient Dense Vector Search within Knowledge Graph Content Embeddings
Benedikt Kantz, Tobias Schreck, Gianmaria Silvello
Knowledge graphs are a core component of today's knowledge infrastructure, supporting reasoning and anchoring knowledge systems to verifiable facts. RDF stores and SPARQL engines f…
Ontology-Driven Structural Regularization for Document-Level Relation Extraction
Laura Menotti, Stefano Marchesin, Gianmaria Silvello
Document-Level Relation Extraction (DocRE) relies heavily on costly manually annotated datasets, while large distant supervision resources such as DocRED distant remain underexploi…
Benchmarking Large Language Models for Knowledge Graph Validation
Farzad Shami, Stefano Marchesin, Gianmaria Silvello
Knowledge Graphs (KGs) store structured factual knowledge by linking entities through relationships, crucial for many applications. These applications depend on the KG's factual ac…
A Domain-Specific Curated Benchmark for Entity and Document-Level Relation Extraction
Marco Martinelli, Stefano Marchesin, Vanessa Bonato +6
Information Extraction (IE), encompassing Named Entity Recognition (NER), Named Entity Linking (NEL), and Relation Extraction (RE), is critical for transforming the rapidly growing…
DOREMI: Optimizing Long Tail Predictions in Document-Level Relation Extraction
Laura Menotti, Stefano Marchesin, Gianmaria Silvello
Document-Level Relation Extraction (DocRE) presents significant challenges due to its reliance on cross-sentence context and the long-tail distribution of relation types, where man…
From Single to Multi-Agent Reasoning: Advancing GeneGPT for Genomics QA
Kimia Abedini, Farzad Shami, Gianmaria Silvello
Comprehending genomic information is essential for biomedical research, yet extracting data from complex distributed databases remains challenging. Large language models (LLMs) off…
Efficient and Reliable Estimation of Named Entity Linking Quality: A Case Study on GutBrainIE
Marco Martinelli, Stefano Marchesin, Gianmaria Silvello
Named Entity Linking (NEL) is a core component of biomedical Information Extraction (IE) pipelines, yet assessing its quality at scale is challenging due to the high cost of expert…
Overview of BioASQ 2025: The Thirteenth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering
Anastasios Nentidis, Georgios Katsimpras, Anastasia Krithara +17
This is an overview of the thirteenth edition of the BioASQ challenge in the context of the Conference and Labs of the Evaluation Forum (CLEF) 2025. BioASQ is a series of internati…
Credible Intervals for Knowledge Graph Accuracy Estimation
Stefano Marchesin, Gianmaria Silvello
Knowledge Graphs (KGs) are widely used in data-driven applications and downstream tasks, such as virtual assistants, recommendation systems, and semantic search. The accuracy of KG…
Testing software for non-discrimination: an updated and extended audit in the Italian car insurance domain
Marco Rondina, Antonio Vetrò, Riccardo Coppola +5
Context. As software systems become more integrated into society's infrastructure, the responsibility of software professionals to ensure compliance with various non-functional req…
Can we measure the impact of a database?
Peter Buneman, Dennis Dosso, Matteo Lissandrini +2
In disseminating scientific and statistical data, on-line databases have almost completely replaced traditional paper-based media such as journals and reference works. Given this,…
Automatic Labels are as Effective as Manual Labels in Biomedical Images Classification with Deep Learning
Niccolò Marini, Stefano Marchesin, Lluis Borras Ferris +12
The increasing availability of biomedical data is helping to design more robust deep learning (DL) algorithms to analyze biomedical samples. Currently, one of the main limitations…
Learning to Rank from Relevance Judgments Distributions
Alberto Purpura, Gianmaria Silvello, Gian Antonio Susto
Learning to Rank (LETOR) algorithms are usually trained on annotated corpora where a single relevance label is assigned to each available document-topic pair. Within the Cranfield…
Algorithmic Fairness Datasets: the Story so Far
Alessandro Fabris, Stefano Messina, Gianmaria Silvello +1
Data-driven algorithms are studied in diverse domains to support critical decisions, directly impacting people's well-being. As a result, a growing community of researchers has bee…
Incentives for Item Duplication under Fair Ranking Policies
Giorgio Maria Di Nunzio, Alessandro Fabris, Gianmaria Silvello +1
Ranking is a fundamental operation in information access systems, to filter information and direct user attention towards items deemed most relevant to them. Due to position bias,…
Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing
Alessandro Fabris, Alan Mishler, Stefano Gottardi +4
We conduct an audit of pricing algorithms employed by companies in the Italian car insurance industry, primarily by gathering quotes through a popular comparison website. While ack…
Gender Stereotype Reinforcement: Measuring the Gender Bias Conveyed by Ranking Algorithms
Alessandro Fabris, Alberto Purpura, Gianmaria Silvello +1
Search Engines (SE) have been shown to perpetuate well-known gender stereotypes identified in psychology literature and to influence users accordingly. Similar biases were found en…