quinex models v0 (ICPSR doi:10.26165/JUELICH-DATA/SXL75G)

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Document Description

Citation

Title:

quinex models v0

Identification Number:

doi:10.26165/JUELICH-DATA/SXL75G

Distributor:

Jülich DATA

Date of Distribution:

2026-01-28

Version:

1

Bibliographic Citation:

Göpfert, Jan; Kuckertz, Patrick; Weinand, Jann M.; Pflugradt, Noah; Linßen, Jochen, 2026, "quinex models v0", https://doi.org/10.26165/JUELICH-DATA/SXL75G, Jülich DATA, V1

Study Description

Citation

Title:

quinex models v0

Identification Number:

doi:10.26165/JUELICH-DATA/SXL75G

Authoring Entity:

Göpfert, Jan (Forschungszentrum Jülich GmbH, Institute of Climate and Energy Systems, Jülich Systems Analysis; RWTH Aachen University, Faculty of Mechanical Engineering)

Kuckertz, Patrick (Forschungszentrum Jülich GmbH, Institute of Climate and Energy Systems, Jülich Systems Analysis)

Weinand, Jann M. (Forschungszentrum Jülich GmbH, Institute of Climate and Energy Systems, Jülich Systems Analysis)

Pflugradt, Noah (Forschungszentrum Jülich GmbH, Institute of Climate and Energy Systems, Jülich Systems Analysis)

Linßen, Jochen (Forschungszentrum Jülich GmbH, Institute of Climate and Energy Systems, Jülich Systems Analysis)

Distributor:

Jülich DATA

Access Authority:

Göpfert, Jan

Depositor:

Göpfert, Jan

Date of Deposit:

2026-01-27

Study Scope

Keywords:

Computer and Information Science, large language models, LLM, transformer, information extraction, quantitative information extraction, measurement extraction, quantity span identification

Abstract:

Transformer models fine-tuned for quantitative information extraction from text

Methodology and Processing

Sources Statement

Data Access

Notes:

All models but one are licensed under Apache-2.0. See the individual model pages for more information.

Other Study Description Materials

Related Publications

Citation

Bibliographic Citation:

Göpfert, J., Kuckertz, P., Müller, G., Lütz, L., Körner., C., Khuat, H., Stolten, D., and Weinand, J.M. "Quinex: Quantitative Information Extraction from Text using Open and Lightweight LLMs"