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20212026
most citedMining experimental data from Materials Science literature with Large Language Models: an evaluation study

27 citations · 81 across the 12 of their papers we have counts for

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7 papers · 1 filter

cs.CL2026

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…

cs.CL2026

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…

cs.DL2026

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…

physics.soc-ph2026

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…

cs.DL2026

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…

cs.CL2026

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…

cs.CL2026

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…