27 citations · 81 across the 12 of their papers we have counts for
12 papers
Layout-Guided Masking for GROBID: Lightweight Structural Gains in Large-Scale Scientific PDF Ingestion
Luca Foppiano, Sana Khamassi, Vipul Gupta
Transforming scholarly PDFs into machine-readable fulltext remains a bottleneck for large-scale information systems. Recent vision-based parsers improve accuracy, but need GPUs and…
Counting Documents Is Not Counting Text: Unit Bias in Web-PDF Corpus Statistics
Luca Foppiano
PDF corpora advertise their size in tokens, but every rate they publish (coverage, OCR routing, re-fetch recovery, language mix) is computed per document, and none decomposes its t…
The INRIA DataLake: A Generic and Scalable Ecosystem of Pipelines for HAL Applied to Software Mentions Tracking
Luca Foppiano, Vipul Gupta, Samuel Scalbert +5
Research repositories contain a large amount of scientific knowledge, but access to structured articles and specialised information, such as datasets or software metadata, remains…
Measuring What the Crawler Sees: Discovery Curves, Core Persistence, and Shell Dynamics in Longitudinal Web Crawls
Michael Paris, Hande Celikkanat, Luca Foppiano
A longitudinal web crawl is a sequence of partial samples of an evolving URL population. Pairwise containment between two crawls is the standard probe; under a simple \emph{urn} mo…
Digging Up Citations: FOSSIL, a Dataset and Workflow for Reference Extraction in Law and the Humanities
Luca Foppiano, Christian Boulanger
Citation extraction tools are designed for the structured end-of-document bibliographies of the natural sciences, but law and humanities scholarship cites references primarily in f…
Construction of a Battery Research Knowledge Graph using a Global Open Catalog
Luca Foppiano, Sae Dieb, Malik Zain +3
Battery research is a rapidly growing and highly interdisciplinary field, making it increasingly difficult to track relevant expertise and identify potential collaborators across i…
CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data
Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94
Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…
SciLaD: A Large-Scale, Transparent, Reproducible Dataset for Natural Scientific Language Processing
Luca Foppiano, Sotaro Takeshita, Pedro Ortiz Suarez +6
SciLaD is a novel, large-scale dataset of scientific language constructed entirely using open-source frameworks and publicly available data sources. It comprises a curated English…
Mining experimental data from Materials Science literature with Large Language Models: an evaluation study
Luca Foppiano, Guillaume Lambard, Toshiyuki Amagasa +1
This study is dedicated to assessing the capabilities of large language models (LLMs) such as GPT-3.5-Turbo, GPT-4, and GPT-4-Turbo in extracting structured information from scient…
Semi-automatic staging area for high-quality structured data extraction from scientific literature
Luca Foppiano, Tomoya Mato, Kensei Terashima +7
We propose a semi-automatic staging area for efficiently building an accurate database of experimental physical properties of superconductors from literature, called SuperCon2, to…
Automatic extraction of materials and properties from superconductors scientific literature
Luca Foppiano, Pedro Baptista de Castro, Pedro Ortiz Suarez +3
The automatic extraction of materials and related properties from the scientific literature is gaining attention in data-driven materials science (Materials Informatics). In this p…
SuperMat: Construction of a linked annotated dataset from superconductors-related publications
Luca Foppiano, Sae Dieb, Akira Suzuki +9
A growing number of papers are published in the area of superconducting materials science. However, novel text and data mining (TDM) processes are still needed to efficiently acces…