mlsanityData to 7 Oct 2026

An Extreme Multi-label Text Classification (XMTC) Library Dataset: What if we took "Use of Practical AI in Digital Libraries" seriously?

arXiv 2603.10876 ↗First posted 11 Mar 2026cs.CL cs.AI cs.DLcited by 2

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Abstract (arXiv)

Subject indexing is vital for discovery but hard to sustain at scale and across languages. We release a large bilingual (English/German) corpus of catalog records annotated with the Integrated Authority File (GND), plus a machine-actionable GND taxonomy. The resource enables ontology-aware multi-label classification, mapping text to authority terms, and agent-assisted cataloging with reproducible, authority-grounded evaluation. We provide a brief statistical profile and qualitative error analyses of three systems. We invite the community to assess not only accuracy but usefulness and transparency, toward authority-anchored AI co-pilots that amplify catalogers' work.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 16 of its 56 references that are in the map. First posted on arXiv 11 Mar 2026.

Builds on

16 of 56 references.

References · 16

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  11. 2025SemEval-2025 Task 5: LLMs4Subjects -- LLM-based Automated Subject Tagging for a National Technical Library's Open-Access Catalogcited by 10
  12. 2025OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology Alignmentcited by 8
4 more
  1. 2025Homa at SemEval-2025 Task 5: Aligning Librarian Records with OntoAligner for Subject Taggingcited by 2
  2. 2025Annif at the GermEval-2025 LLMs4Subjects Task: Traditional XMTC Augmented by Efficient LLMscited by 2
  3. 2025TartuNLP at SemEval-2025 Task 5: Subject Tagging as Two-Stage Information Retrievalcited by 1
  4. 2025NBF at SemEval-2025 Task 5: Light-Burst Attention Enhanced System for Multilingual Subject Recommendationcited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026A Skill-Based AI Agentic Pipeline for Library of Congress Subject Indexingcited by 1
  2. 2026Does generative AI supersede supervised XMLC? A Benchmark Study on Automated Subject Indexing with German Scientific Literaturecited by 0