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New framework improves funder name disambiguation in research publications

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework for disambiguating funder names in scientific publication records, addressing challenges like spelling variations and abbreviations. By integrating datasets from the Research Organization Registry (ROR), Web of Science (WoS), and Crossref Open Funder Registry (OFR), they created a training dataset. Fine-tuning open-weight embedding models using multi-task learning, their best models achieved over 0.90 accuracy in matching WoS funder names to ROR identifiers, significantly outperforming general-purpose LLMs like GPT-5.2 and Claude Sonnet 4.6. The framework also includes methods for handling funder names not indexed in ROR and highlights difficulties with smaller or non-English-speaking country funders. AI

IMPACT Enhances the ability to track and analyze research funding, potentially improving resource allocation and scientific policy.

RANK_REASON The cluster contains a research paper detailing a new framework and models for a specific NLP task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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New framework improves funder name disambiguation in research publications

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The cluster contains a research paper detailing a new framework and models for a specific NLP task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Kanyao Han, Zhiwen You, Jinseok Kim, Jana Diesner ·

    Multi-Functional Embedding Models for Funder Name Disambiguation in Scientific Publication Records

    arXiv:2609.09984v1 Announce Type: new Abstract: Understanding the historical allocation and distribution of research funding advances our knowledge of how scientific research is supported across fields, institutions, and regions. However, large-scale analyses are hindered by the …

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