5 citations · 8 across the 18 of their papers we have counts for
8 papers · 1 filter
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…