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License: CC BY 4.0

21 to 30 of 48 Results

CA-EN_Parallel_Corpus Nov 3, 2025 - Language Technologies Laboratory De Luca Fornaciari, Francesca; Villegas, Marta; Melero, Maite; Mash, Audrey, 2025, "CA-EN_Parallel_Corpus", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/ERUHKY, BSC Dataverse, V2 The CA-EN Parallel Corpus is a Catalan-English textual dataset of parallel sentences created to support Catalan in NLP tasks, specifically Machine Translation. The dataset can be used to train Bilingual Machine Translation models between English and Catalan in any direction, as well as Multilingual Machine Translation models.
Replication Data for: Beyond the Link: Assessing LLMs’ Ability to Classify Political Content Across Global Media Oct 30, 2025 - COMPASS - COMplex Political And Social Simulations DE LA FUENTE CUESTA, ALEJANDRO; Alberto Martínez Serra; Nienke Visscher; Cardenal, Ana S., 2025, "Replication Data for: Beyond the Link: Assessing LLMs’ Ability to Classify Political Content Across Global Media", https://doi.org/10.82201/8UPPY6, BSC Dataverse, V2, UNF:6:j4VEdzl/g0wp+AX0/Pik1w== [fileUNF] This dataset and replication package accompany the paper: “Beyond the Link: Assessing LLMs’ Ability to Classify Political Content Across Global Media.” by Alejandro De La Fuente-Cuesta, Alberto Martínez-Serra, R. Nienke Visscher, and Ana S. Cardenal (2025). The materials include the data and code necessary to reproduce all analyses presented in the...
Machine learning models for 3D complex shape analysis and classification on the NEBD+ dataset Oct 17, 2025 - Computational Archaeology Berganzo-Besga, Iban, 2025, "Machine learning models for 3D complex shape analysis and classification on the NEBD+ dataset", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/J0HVTR, BSC Dataverse, V1, UNF:6:GSgdAZ4nevEX2NwRGqdJfQ== [fileUNF] This dataset presents diverse models trained using machine learning (ML) like traditional architectures for geometric morphometrics (GMM) such as scikit-learn GBM, KNN, LDA, RF and SVM, more advance ones like XGBoost GBM, and deep learning architectures such as MLP, TabPFN and MeshCNN. The models were trained on the NEBD+ dataset.
NEBD+: Enhanced Northern European Barley Dataset for 3D complex shape analysis and classification. Oct 17, 2025 - Computational Archaeology Berganzo-Besga, Iban; Livarda, Alexandra; Aliende Garcia, Paloma; Wallace, Michael; Orengo, Hector A., 2025, "NEBD+: Enhanced Northern European Barley Dataset for 3D complex shape analysis and classification.", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/ETUHIO, BSC Dataverse, V1, UNF:6:tg5jUfTY6pD8q18Yc/9EDA== [fileUNF] This datasheet describes a new dataset for the tasks of 3D complex shape analysis and classification. The dataset consists of 697 barley grains, grouped into the following categories: six-row Bere (Bere-R6), six-row Scandinavian (Scand-R6), two-row non-Scottish British (Brit-R2), and two-row (non-Bere) Scottish (Scot-R2), all of Orkney and Western...
Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r4 Oct 3, 2025 - Earth Sciences Marc Batlle Martín, 2025, "Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r4", https://doi.org/10.82201/OUCRUQ, BSC Dataverse, V1 This ensemble of 3 historical simulations for the 1990-2014 period has been produced with a 10-km global configuration of IFS-NEMO, the Climate Digital Twin for climate adaptation developed under the Destination Earth initiative of the European Union. This configuration corresponds to the second cycle of the Climate Digital Twin.
Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r3 Oct 2, 2025 - Earth Sciences Marc Batlle Martín, 2025, "Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r3", https://doi.org/10.82201/TE7JWA, BSC Dataverse, V1 This ensemble of 3 historical simulations for the 1990-2014 period has been produced with a 10-km global configuration of IFS-NEMO, the Climate Digital Twin for climate adaptation developed under the Destination Earth initiative of the European Union. This configuration corresponds to the second cycle of the Climate Digital Twin.
Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r2 Sep 30, 2025 - Earth Sciences Marc Batlle Martín, 2025, "Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r2", https://doi.org/10.82201/FPTR5E, BSC Dataverse, V1 This ensemble of 3 historical simulations for the 1990-2014 period has been produced with a 10-km global configuration of IFS-NEMO, the Climate Digital Twin for climate adaptation developed under the Destination Earth initiative of the European Union. This configuration corresponds to the second cycle of the Climate Digital Twin.
XitXat Sep 29, 2025 - Language Technologies Laboratory Rodriguez-Penagos, Carlos; Armentano i Oller, Carme; Villegas, Marta, 2025, "XitXat", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/642QYD, BSC Dataverse, V2 XitXat is a conversational dataset consisting of 950 chatbot–user conversations across 10 different domains. The conversations were created using the Wizard-of-Oz method. User interactions are annotated with intents and relevant slots, following the attached annotation guidelines. The dataset is designed to support research in natural language unde...
EQ-Bench_ca Sep 29, 2025 - Language Technologies Laboratory Rivera Hidalgo de Torralba, Paula; Gonzalez-Agirre, Aitor; Villegas, Marta; Aula-Blasco, Javier; Saiz Antón, José Javier, 2025, "EQ-Bench_ca", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/UECWEX, BSC Dataverse, V2 EQ‑bench_ca is the Catalan translation and linguistic adaptation of EQ‑Bench, a dataset for evaluating emotional reasoning in language models via dialogue prompts. It is intended to reflect how emotional expression and perception vary across languages, enabling evaluation in Catalan.
EQ-bench_es Sep 29, 2025 - Language Technologies Laboratory Saiz Antón, José Javier; Rivera Hidalgo de Torralba, Paula; Gonzalez-Agirre, Aitor; Villegas, Marta; Aula-Blasco, Javier, 2025, "EQ-bench_es", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/PVIYPG, BSC Dataverse, V3 EQ‑bench_es is the Spanish translation and adaptation of EQ‑Bench, designed for evaluating emotional reasoning in language models via dialogue prompts in Spanish.

CA-EN_Parallel_Corpus

Nov 3, 2025 - Language Technologies Laboratory

De Luca Fornaciari, Francesca; Villegas, Marta; Melero, Maite; Mash, Audrey, 2025, "CA-EN_Parallel_Corpus", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/ERUHKY, BSC Dataverse, V2

The CA-EN Parallel Corpus is a Catalan-English textual dataset of parallel sentences created to support Catalan in NLP tasks, specifically Machine Translation. The dataset can be used to train Bilingual Machine Translation models between English and Catalan in any direction, as well as Multilingual Machine Translation models.

Replication Data for: Beyond the Link: Assessing LLMs’ Ability to Classify Political Content Across Global Media

Oct 30, 2025 - COMPASS - COMplex Political And Social Simulations

DE LA FUENTE CUESTA, ALEJANDRO; Alberto Martínez Serra; Nienke Visscher; Cardenal, Ana S., 2025, "Replication Data for: Beyond the Link: Assessing LLMs’ Ability to Classify Political Content Across Global Media", https://doi.org/10.82201/8UPPY6, BSC Dataverse, V2, UNF:6:j4VEdzl/g0wp+AX0/Pik1w== [fileUNF]

This dataset and replication package accompany the paper: “Beyond the Link: Assessing LLMs’ Ability to Classify Political Content Across Global Media.” by Alejandro De La Fuente-Cuesta, Alberto Martínez-Serra, R. Nienke Visscher, and Ana S. Cardenal (2025). The materials include the data and code necessary to reproduce all analyses presented in the...

Machine learning models for 3D complex shape analysis and classification on the NEBD+ dataset

Oct 17, 2025 - Computational Archaeology

Berganzo-Besga, Iban, 2025, "Machine learning models for 3D complex shape analysis and classification on the NEBD+ dataset", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/J0HVTR, BSC Dataverse, V1, UNF:6:GSgdAZ4nevEX2NwRGqdJfQ== [fileUNF]

This dataset presents diverse models trained using machine learning (ML) like traditional architectures for geometric morphometrics (GMM) such as scikit-learn GBM, KNN, LDA, RF and SVM, more advance ones like XGBoost GBM, and deep learning architectures such as MLP, TabPFN and MeshCNN. The models were trained on the NEBD+ dataset.

NEBD+: Enhanced Northern European Barley Dataset for 3D complex shape analysis and classification.

Oct 17, 2025 - Computational Archaeology

Berganzo-Besga, Iban; Livarda, Alexandra; Aliende Garcia, Paloma; Wallace, Michael; Orengo, Hector A., 2025, "NEBD+: Enhanced Northern European Barley Dataset for 3D complex shape analysis and classification.", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/ETUHIO, BSC Dataverse, V1, UNF:6:tg5jUfTY6pD8q18Yc/9EDA== [fileUNF]

This datasheet describes a new dataset for the tasks of 3D complex shape analysis and classification. The dataset consists of 697 barley grains, grouped into the following categories: six-row Bere (Bere-R6), six-row Scandinavian (Scand-R6), two-row non-Scottish British (Brit-R2), and two-row (non-Bere) Scottish (Scot-R2), all of Orkney and Western...

Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r4

Oct 3, 2025 - Earth Sciences

Marc Batlle Martín, 2025, "Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r4", https://doi.org/10.82201/OUCRUQ, BSC Dataverse, V1

This ensemble of 3 historical simulations for the 1990-2014 period has been produced with a 10-km global configuration of IFS-NEMO, the Climate Digital Twin for climate adaptation developed under the Destination Earth initiative of the European Union. This configuration corresponds to the second cycle of the Climate Digital Twin.

Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r3

Oct 2, 2025 - Earth Sciences

Marc Batlle Martín, 2025, "Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r3", https://doi.org/10.82201/TE7JWA, BSC Dataverse, V1

Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r2

Sep 30, 2025 - Earth Sciences

Marc Batlle Martín, 2025, "Ensemble of historical simulations at 10km resolution with IFS-NEMO [Cycle 2 of the Climate DT] - member r2", https://doi.org/10.82201/FPTR5E, BSC Dataverse, V1

XitXat

Sep 29, 2025 - Language Technologies Laboratory

Rodriguez-Penagos, Carlos; Armentano i Oller, Carme; Villegas, Marta, 2025, "XitXat", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/642QYD, BSC Dataverse, V2

XitXat is a conversational dataset consisting of 950 chatbot–user conversations across 10 different domains. The conversations were created using the Wizard-of-Oz method. User interactions are annotated with intents and relevant slots, following the attached annotation guidelines. The dataset is designed to support research in natural language unde...

EQ-Bench_ca

Sep 29, 2025 - Language Technologies Laboratory

Rivera Hidalgo de Torralba, Paula; Gonzalez-Agirre, Aitor; Villegas, Marta; Aula-Blasco, Javier; Saiz Antón, José Javier, 2025, "EQ-Bench_ca", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/UECWEX, BSC Dataverse, V2

EQ‑bench_ca is the Catalan translation and linguistic adaptation of EQ‑Bench, a dataset for evaluating emotional reasoning in language models via dialogue prompts. It is intended to reflect how emotional expression and perception vary across languages, enabling evaluation in Catalan.

EQ-bench_es

Sep 29, 2025 - Language Technologies Laboratory

Saiz Antón, José Javier; Rivera Hidalgo de Torralba, Paula; Gonzalez-Agirre, Aitor; Villegas, Marta; Aula-Blasco, Javier, 2025, "EQ-bench_es", https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/PVIYPG, BSC Dataverse, V3

EQ‑bench_es is the Spanish translation and adaptation of EQ‑Bench, designed for evaluating emotional reasoning in language models via dialogue prompts in Spanish.

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