Skip to main content
Ir a la página de inicio de la Comisión Europea (se abrirá en una nueva ventana)
español español
CORDIS - Resultados de investigaciones de la UE
CORDIS

AI-CODE - AI services for COntinuous trust in emerging Digital Environments

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Prototyping the disinformation detection and next generation of social media services (se abrirá en una nueva ventana)

Initial versions of the disinformation detection services focusing on next generation social media, as carried out in T4.1

Prototype version of Dynamic Simulator for Media Professionals (se abrirá en una nueva ventana)

Initial -prototype of the interactive simulator for media professionals allowing users to observe selected functionalities of the simulator and give feedback regarding its design.

Prototyping the Media Asset Annotation and Management (MAAM) service (se abrirá en una nueva ventana)

Initial versions of services that were built and prototyped in T4.3.

Prototype version of the Personal Companion for media professionals service (se abrirá en una nueva ventana)

Initial version of the Personal Companion for understanding disinformation for media professionals service.

Prototyping the Trustability and credibility assessment services (se abrirá en una nueva ventana)

First prototype of the Trustability and credibility assessment services produced in T4.2

Prototyping transparency services for AI-model cards (se abrirá en una nueva ventana)

Initial versions of transparency services for AI-model cards carried out in T6.2

Quality Plan (se abrirá en una nueva ventana)

This deliverable will state all the quality procedures to guarantee a successful project implementation.

Adaptation of existing credibility and trust assessment and disinformation detection tools to next-generation social media and AI-generated content (se abrirá en una nueva ventana)

On the basis of T2.4, this deliverable will complement previous two deliverables and provide recommendations for development of AI-CODE services.

Data Management Plan (se abrirá en una nueva ventana)

This deliverable will describe how the AI-CODE project manages data throughout its life cycle, in order to be compliant to the regulatory framework.

Functional specifications and technical requirements (se abrirá en una nueva ventana)

Description of the necessary functionalities and technical requirements of the AI-CODE services based on results from tasks T3.3 und T3.4.

Report on the assessment of the role of novel text and image generative AI methodologies in producing and combating disinformation (se abrirá en una nueva ventana)

This deliverable will summarise the research performed in T2.2 and T2.3 and describe positive as well as negative consequences of generative AI adopted in social media.

Impact master plan (se abrirá en una nueva ventana)

Document detailing the project dissemination, and communication plan, outlining the target groups and relevant tailored outreach strategies and the project communication channels.

User-centred requirements definition (se abrirá en una nueva ventana)

Requirements definition for the defined user groups and use case scenarios based on results of the analysis in T3.1, T3.2 and T3.4.

Report on technological and socio-behavioural characterization of next-generation social media (se abrirá en una nueva ventana)

This deliverable will summarise the research performed in T2.1 and outline the emerging trust and disinformation risks.

Publicaciones

LLMs vs Established Text Augmentation Techniques for Classification: When do the Benefits Outweight the Costs? (se abrirá en una nueva ventana)

Autores: Čegiň, Ján; Simko, Jakub; Brusilovsky, Peter
Publicado en: Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (NAACL 2025), 2025
Editor: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2408.16502

Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation (se abrirá en una nueva ventana)

Autores: Jan Cegin, Branislav Pecher, Jakub Simko, Ivan Srba, Maria Bielikova, Peter Brusilovsky
Publicado en: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2024.acl-long.710

Authorship Obfuscation in Multilingual Machine-Generated Text Detection (se abrirá en una nueva ventana)

Autores: Macko, Dominik; Moro, Robert; Uchendu, Adaku; Srba, Ivan; Lucas, Jason Samuel; Yamashita, Michiharu; Tripto, Nafis Irtiza; Lee, Dongwon; Simko, Jakub; Bielikova, Maria
Publicado en: Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Editor: Association for Computational Linguistics
DOI: 10.48550/arXiv.2401.07867

SIDBench: A Python framework for reliably assessing synthetic image detection methods (se abrirá en una nueva ventana)

Autores: Manos Schinas, Symeon Papadopoulos
Publicado en: 3rd ACM International Workshop on Multimedia AI against Disinformation, 2024
Editor: ACM
DOI: 10.1145/3643491.3660277

ModaFact: Multi-paradigm Evaluation for Joint Event Modality and Factuality Detection

Autores: Rovera, Marco; Cristoforetti, Serena; Tonelli,Sara
Publicado en: Proceedings of the 31st International Conference on Computational Linguistics, 2025
Editor: Association for Computational Linguistics

A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Texts (se abrirá en una nueva ventana)

Autores: Tripto, Nafis Irtiza; Venkatraman, Saranya; Macko, Dominik; Moro, Robert; Srba, Ivan; Uchendu, Adaku; Le, Thai; Lee, Dongwon
Publicado en: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Editor: Association for Computational Linguistics
DOI: 10.48550/arXiv.2311.08374

MultiSocial: Multilingual Benchmark of Machine-Generated Text Detection of Social-Media Texts (se abrirá en una nueva ventana)

Autores: Dominik Macko, Jakub Kopál, Robert Moro, Ivan Srba
Publicado en: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Editor: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2406.12549

KInIT at SemEval-2024 Task 8: Fine-tuned LLMs for Multilingual Machine-Generated Text Detection (se abrirá en una nueva ventana)

Autores: Spiegel, Michal; Macko, Dominik
Publicado en: Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), 2024
Editor: Association for Computational Linguistics
DOI: 10.48550/arXiv.2402.13671

Buscando datos de OpenAIRE...

Se ha producido un error en la búsqueda de datos de OpenAIRE

No hay resultados disponibles

Mi folleto 0 0