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CORDIS - Risultati della ricerca dell’UE
CORDIS

Improving scientific excellence and creativity in combating disinformation with artificial intelligence and language technologies

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Data management plan – Version 1 (si apre in una nuova finestra)

The first version of the data management plan (DMP) will be prepared by M6 to outline how the research data are collected or generated and will be handled during a project, and after it is completed, describe what data will be collected/generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved. The DMP is a living document: it will be updated by the end of each reporting period. DMP includes: (1) What data will be collected/generated; (2) What standards will be used; (3) What types and format of data will be created; (4) How will metadata be generated; (5) How will the data be documented; (6) What data will be exploited, shared, made open; (7) How and by whom will data be curated and preserved.

Data management plan – Version 3 (si apre in una nuova finestra)

The final version of the data management plan (DMP) will be prepared by M30 to outline how the research data has been collected or generated by this point in the project and will be further handled after it is completed, whether and how this data will be shared and/or made open, and how it will be curated and preserved.

Data management plan – Version 2 (si apre in una nuova finestra)

The second updated version of the data management plan (DMP) will be prepared by M17 to outline how the research data is collected or generated by this point in the project and will be further handled during a project, and after it is completed, describe what data will be collected/generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved.

Plan for dissemination and exploitation including communication – Version 1 (si apre in una nuova finestra)

The document will outline the initial version of the detailed planning of the dissemination and communication activities in a systematic manner, with the aim of performing actions and campaigns that reach specific groups and audiences for specific purposes. The plan will also address the exploitation and sustainability aspects, ensuring the timely promotion of the project’s outcomes and engagement of parties outside the Consortium, interested to use or adopt them.

Shared task report (si apre in una nuova finestra)

The report will consist of the description of the implementation and results of the shared task utilising a dataset created within the project. The task will be open to individual researchers (with focus on doctoral and postdoctoral researchers) as well as small teams also from external researchers. The shared task participants will be invited to submit their results and the best performing ones also a paper. Individual and general results of participants will be also included to the report.

Plan for dissemination and exploitation including communication – Version 2 (si apre in una nuova finestra)

The document will outline the final detailed planning of the dissemination and communication activities in a systematic manner, with the aim of performing actions and campaigns that reach specific groups and audiences for specific purposes. The plan will also address the exploitation and sustainability aspects based on the project's results at the time, ensuring the timely promotion of the project’s outcomes and engagement of parties outside the Consortium, interested to use or adopt them.

Summer school report (si apre in una nuova finestra)

The report will describe the organizing and results of the Summer School on Trustworthy AI and NLP, which will take place in Slovakia. The summer school will be open to doctoral students, master's students in the last year of their study, and postdoctoral researchers within 3 years after receiving their Ph.D. degree. The study programme and summer school results will also be included to the report.

Report on CLARIN integration and other liaison activities (si apre in una nuova finestra)

The report will outline the results of the implementation of the measures aimed at improving the visibility and integration of KInIT in major European LT initiatives and bodies, which include: active engagement in major LT bodies and projects, and linking with major LT industry associations.

Report on dissemination, communication and synergy activities – Version 1 (si apre in una nuova finestra)

The report will outline the mid-term results of dissemination and communication activities in a systematic manner listing the performed actions and campaigns that reach specific groups and audiences for specific purposes. The report will also address the exploitation and sustainability mid-term results, focusing on the outcomes of promotion of the project’s outcomes and engagement of parties outside the Consortium, interested to use or adopt them.

Ethics, innovation and IPR management plan (si apre in una nuova finestra)

The document will describe the planned measures for IPR management, as well as ethics and innovation management. The followed policies like the Open Science policy will be mentioned.

Scientific webinar series report (si apre in una nuova finestra)

The report will include information about the implementation of four webinars (online expert lectures followed by a discussion and knowledge sources sharing) and the results thereof (list of participants, presenters, topics discussed, feedback, and lessons learned). The webinars will cover the topics of disinformation combating, multimodal AI, multilingual AI and trustworthy AI.

Training report on research management support and operation (si apre in una nuova finestra)

The report will include the description and results of the physical workshops or virtual webinars on the topic of research management support and operation, which will include the overall description of the topic, the organizational matters, participants list, outcomes, and lessons learned.

Training report on opportunity seeking and scientific proposal writing (si apre in una nuova finestra)

The report will include the description and results of the physical workshops or virtual webinars on the topic of opportunity-seeking and proposal writing, which will include the overall description of the topic, the organizational matters, participants list, outcomes, and lessons learned.

Replication challenge report (si apre in una nuova finestra)

The report will describe the organization and results of the replication challenge targeted at doctoral students. Each involved student will be assigned a mentor from the leading partners. Together they will select a scientific paper (related to the project topic) and replicate the research described therein. The process and results of individual projects' realization will also be included in the report.

Report on dissemination, communication and synergy activities – Version 2 (si apre in una nuova finestra)

The report will outline the final results of dissemination and communication activities in a systematic manner listing the performed actions and campaigns that reach specific groups and audiences for specific purposes. The report will also address the exploitation and sustainability mid-term results, focusing on the outcomes of promotion of the project’s outcomes and engagement of parties outside the Consortium, interested to use or adopt them.

Training report on innovation, technology transfer and networking (si apre in una nuova finestra)

The report will include the description and results of the physical workshops or virtual webinars on the topic of innovation, technology transfer, and networking, which will include the overall description of the topic, the organizational matters, participants list, outcomes, and lessons learned.

Collected labelled dataset (si apre in una nuova finestra)

The dataset with accompanying description including labelling scheme and selected quantitative characteristics. Data collection will include several approaches, e.g., automatic content crawling, crowdsourcing or using human experts to annotate data, based on requirements for various tasks. Data collected will be used to answer research questions posed in tasks 2.2-2.4 and will be treated following the FAIR principles.

AI methods for claim matching (si apre in una nuova finestra)

The consortium will develop novel machine learning methods for multilingual claim matching, utilizing data from source languages to perform claim matching in target languages. The methods developed will be mainly based on foundation multilingual language models and will derive from these.

Visuals and branding materials (si apre in una nuova finestra)

The plan will have a description of brand identity and visuals; website including a splash page; promotional material (brochure/leaflet, poster, roll-up, slides, poster, promo video); communication materials (press releases, newsletters, and additional mass mailing, “exploitation booster materials” to our target groups/stakeholders, aiming to contribute to its use and to maximize the impact of the project; social Media (SNS) management.

Pubblicazioni

nvestigating Language and Retrieval Bias in Multilingual Previously Fact-Checked Claim Detection

Autori: Ivan Vykopal, Antonia Karamolegkou, Jaroslav Kopčan, Qiwei Peng, Tomáš Javůrek, Michal Gregor, Marián Šimko
Pubblicato in: 2025
Editore: Association for Computational Linguistics

o-MEGA: Optimized Methods for Explanation Generation and Analysis

Autori: Ľuboš Kriš, Jaroslav Kopčan, Qiwei Peng, Andrej Ridzik, Marcel Veselý, Martin Tamajka
Pubblicato in: 2025
Editore: Association for Computational Linguistics

HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization (si apre in una nuova finestra)

Autori: Peng, Qiwei; Chai, Yekun; Li, Xuhong
Pubblicato in: 2024
Editore: International Committee on Computational Linguistics
DOI: 10.48550/arXiv.2402.16694

Tokenization Falling Short: On Subword Robustness in Large Language Models (si apre in una nuova finestra)

Autori: Chai, Yekun; Fang, Yewei; Peng, Qiwei; Li, Xuhong
Pubblicato in: Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2406.11687

Large Language Models for Multilingual Previously Fact-Checked Claim Detection (si apre in una nuova finestra)

Autori: Ivan Vykopal, Matúš Pikuliak, Simon Ostermann, Tatiana Anikina, Michal Gregor, Marian Simko
Pubblicato in: Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
Editore: Association for Computational Linguistics
DOI: 10.18653/V1/2025.FINDINGS-EMNLP.852

Women Are Beautiful, Men Are Leaders: Gender Stereotypes in Machine Translation and Language Modeling (si apre in una nuova finestra)

Autori: Matúš Pikuliak, Stefan Oresko, Andrea Hrckova, Marian Simko
Pubblicato in: Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Editore: Association for Computational Linguistics
DOI: 10.18653/V1/2024.FINDINGS-EMNLP.173

Concept Space Alignment in Multilingual LLMs (si apre in una nuova finestra)

Autori: Peng, Qiwei; Søgaard, Anders
Pubblicato in: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2410.01079

Multimodal and Multilingual Fact-Checked Article Retrieval (si apre in una nuova finestra)

Autori: Stefanos-Iordanis Papadopoulos, Ivana Beňová, Sebastian Kula, Michal Gregor, George Karantaidis, Tomáš Javůrek, Marián Šimko, Symeon Papadopoulos
Pubblicato in: Proceedings of the 2025 International Conference on Multimedia Retrieval, 2025
Editore: ACM
DOI: 10.1145/3731715.3733402

GrEmLIn: A Repository of Green Baseline Embeddings for 87 Low-Resource Languages Injected with Multilingual Graph Knowledge (si apre in una nuova finestra)

Autori: Daniil Gurgurov; Rishu Kumar; Simon Ostermann 0002
Pubblicato in: Findings of the Association for Computational Linguistics: NAACL 2025, 2025
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2409.18193

Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance (si apre in una nuova finestra)

Autori: Pecher, Branislav; Srba, Ivan; Bielikova, Maria
Pubblicato in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2402.12819

Only for the Unseen Languages, Say the Llamas: On the Efficacy of Language Adapters for Cross-lingual Transfer in English-centric LLMs (si apre in una nuova finestra)

Autori: Julian Schlenker, Jenny Kunz, Tatiana Anikina, Günter Neumann, Simon Ostermann
Pubblicato in: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), 2025
Editore: Association for Computational Linguistics
DOI: 10.18653/V1/2025.ACL-SRW.62

Multilingual Previously Fact-Checked Claim Retrieval (si apre in una nuova finestra)

Autori: Pikuliak, Matúš; Srba, Ivan; Moro, Robert; Hromadka, Timo; Smolen, Timotej; Melisek, Martin; Vykopal, Ivan; Simko, Jakub; Podrouzek, Juraj; Bielikova, Maria
Pubblicato in: 2023
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2305.07991

A Rigorous Evaluation of LLM Data Generation Strategies for Low-Resource Languages (si apre in una nuova finestra)

Autori: Tatiana Anikina, Jan Cegin, Jakub Simko, Simon Ostermann
Pubblicato in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025
Editore: Association for Computational Linguistics
DOI: 10.18653/V1/2025.EMNLP-MAIN.418

SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval

Autori: Qiwei Peng, Robert Moro, Michal Gregor, Ivan Srba, Simon Ostermann, Marian Simko, Juraj Podrouzek, Matúš Mesarčík, Jaroslav Kopčan, Anders Søgaard
Pubblicato in: 2025
Editore: Association for Computational Linguistics

Understanding Subword Compositionality of Large Language Models

Autori: Qiwei Peng, Yekun Chai, Anders Søgaard
Pubblicato in: 2025
Editore: Association for Computational Linguistics

Beyond Image-Text Matching: Verb Understanding in Multimodal Transformers Using Guided Masking (si apre in una nuova finestra)

Autori: Ivana Benová; Jana Kosecka; Michal Gregor; Martin Tamajka; Marcel Veselý; Marián Simko
Pubblicato in: Lecture Notes in Computer Science ISBN: 9783031826696, 2025
DOI: 10.1007/978-3-031-82670-2_7

Credible, Unreliable or Leaked?: Evidence verification for enhanced automated fact checking (si apre in una nuova finestra)

Autori: Chrysidis Z.; Papadopoulos S. I.; Papadopoulos S.; Petrantonakis P.
Editore: The Association for Computing Machinery
DOI: 10.1145/3643491.3660278

LLMs vs Established Text Augmentation Techniques for Classification: When do the Benefits Outweight the Costs?

Autori: Jan Cegin, Jakub Simko, Peter Brusilovsky
Pubblicato in: 2025
Editore: Association for Computational Linguistics

Soft Language Prompts for Language Transfer (si apre in una nuova finestra)

Autori: Ivan Vykopal; Simon Ostermann 0002; Marián Simko
Pubblicato in: 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), 2025
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2407.02317

Assessing Web Search Credibility and Response Groundedness in Chat Assistants

Autori: Ivan Vykopal, Matúš Pikuliak, Simon Ostermann, Marián Šimko
Pubblicato in: Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2025
Editore: Association for Computational Linguistics

skLEP: A Slovak General Language Understanding Benchmark

Autori: Marek Suppa, Andrej Ridzik, Daniel Hládek, Tomáš Javůrek, Viktória Ondrejová, Kristína Sásiková, Martin Tamajka, Marian Simko
Pubblicato in: 2025
Editore: Association for Computational Linguistics

Pessimistic Off-Policy Optimization for Learning to Rank (si apre in una nuova finestra)

Autori: Matej Cief, Branislav Kveton, Michal Kompan
Pubblicato in: Frontiers in Artificial Intelligence and Applications, ECAI 2024, 2024
Editore: IOS Press
DOI: 10.3233/FAIA240703

In-Depth Look at Word Filling Societal Bias Measures (si apre in una nuova finestra)

Autori: Pikuliak, Matúš; Beňová, Ivana; Bachratý, Viktor
Pubblicato in: 2023
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2302.12640

Small Models, Big Impact: Efficient Corpus and Graph-Based Adaptation of Small Multilingual Language Models for Low-Resource Languages

Autori: Daniil Gurgurov, Ivan Vykopal, Josef Van Genabith, Simon Ostermann
Pubblicato in: 2025
Editore: Association for Computational Linguistics

On Multilingual Encoder Language Model Compression for Low-Resource Languages

Autori: Daniil Gurgurov, Michal Gregor, Josef Van Genabith, Simon Ostermann
Pubblicato in: 2025
Editore: Association for Computational Linguistics

Debiasing Multilingual LLMs in Cross-lingual Latent Space (si apre in una nuova finestra)

Autori: Qiwei Peng, Guimin Hu, Yekun Chai, Anders Søgaard
Pubblicato in: 2025
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2508.17948

Adapting Multilingual LLMs to Low-Resource Languages with Knowledge Graphs via Adapters (si apre in una nuova finestra)

Autori: Daniil Gurgurov; Mareike Hartmann; Simon Ostermann 0002
Pubblicato in: Proceedings of the 1st Workshop on Knowledge Graphs and Large Language Models (KaLLM 2024), 2024
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2407.01406

Disinformation Capabilities of Large Language Models (si apre in una nuova finestra)

Autori: Ivan Vykopal, Matúš Pikuliak, Ivan Srba, Robert Moro, Dominik Macko, Maria Bielikova
Pubblicato in: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Editore: Association for Computational Linguistics
DOI: 10.18653/V1/2024.ACL-LONG.793

CV-Probes: Studying the interplay of lexical and world knowledge in visually grounded verb understanding (si apre in una nuova finestra)

Autori: Benova, Ivana; Gregor, Michal; Gatt, Albert
Pubblicato in: CoRR, 2024
Editore: CogSci 2025
DOI: 10.48550/ARXIV.2409.01389

On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices (si apre in una nuova finestra)

Autori: Branislav Pecher; Ivan Srba; Mária Bieliková
Pubblicato in: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2402.12817

Similarity Over Factuality: Are we Making Progress on Multimodal Out-of-Context Misinformation Detection?

Autori: Stefanos-Iordanis Papadopoulos, Christos Koutlis, Symeon Papadopoulos, Panagiotis C. Petrantonakis
Pubblicato in: 2025
Editore: IEEE/CVF

Cross-Validated Off-Policy Evaluation (si apre in una nuova finestra)

Autori: Matej Cief; Branislav Kveton; Michal Kompan
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, 2025
Editore: AAAI Press
DOI: 10.48550/ARXIV.2405.15332

Average Is Not Enough: Caveats of Multilingual Evaluation (si apre in una nuova finestra)

Autori: Pikuliak, Matúš; Šimko, Marián
Pubblicato in: 2023
Editore: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2301.01269

On Training Data Influence of GPT Models (si apre in una nuova finestra)

Autori: Qingyi Liu; Yekun Chai; Shuohuan Wang; Yu Sun 0004; Qiwei Peng 0002; Keze Wang; Hua Wu 0003
Pubblicato in: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Editore: EMNLP 2024
DOI: 10.48550/ARXIV.2404.07840

dfkinit2b at CheckThat! 2025: Leveraging LLMs and Ensemble of Methods for Multilingual Claim Normalization

Autori: Tatiana Anikina, Ivan Vykopal, Sebastian Kula, Ravi Kiran Chikkala, Natalia Skachkova, Jing Yang, Veronika Solopova, Vera Schmitt, Simon Ostermann
Pubblicato in: 2025
Editore: CEUR

Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation (si apre in una nuova finestra)

Autori: Jan Cegin, Branislav Pecher, Jakub Simko, Ivan Srba, Maria Bielikova, Peter Brusilovsky
Pubblicato in: Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
Editore: Association for Computational Linguistics
DOI: 10.18653/V1/2025.FINDINGS-EMNLP.296

Automatic Fact-checking in English and Telugu

Autori: Ravikiran Chikkala, Tatiana Anikina, Natalia Skachkova, Ivan Vykopal, Rodrigo Agerri, Josef van Genabith
Pubblicato in: 2025
Editore: INCOMA Ltd., Shoumen, Bulgaria

'Humor, Art, or Misinformation?': A Multimodal Dataset for Intent-Aware Synthetic Image Detection (si apre in una nuova finestra)

Autori: Anastasios Skoularikis, Stefanos-Iordanis Papadopoulos, Symeon Papadopoulos, Panagiotis C. Petrantonakis
Pubblicato in: Proceedings of the 2nd International Workshop on Diffusion of Harmful Content on Online Web, 2025
Editore: ACM
DOI: 10.1145/3746275.3762215

Task Prompt Vectors: Effective Initialization Through Multi-task Soft Prompt Transfer (si apre in una nuova finestra)

Autori: Róbert Belanec; Simon Ostermann 0002; Ivan Srba; Mária Bieliková
Pubblicato in: Lecture Notes in Computer Science ISBN 9783662722428, 2025
Editore: Springer-Verlag
DOI: 10.48550/ARXIV.2408.01119

Multilingual Political Views of Large Language Models: Identification and Steering

Autori: Daniil Gurgurov, Katharina Trinley, Ivan Vykopal, Josef Van Genabith, Simon Ostermann, Roberto Zamparelli
Pubblicato in: 2025
Editore: Association for Computational Linguistics

Language Arithmetics: Towards Systematic Language Neuron Identification and Manipulation

Autori: Daniil Gurgurov, Katharina Trinley, Yusser Al Ghussin, Tanja Baeumel, Josef Van Genabith, Simon Ostermann
Pubblicato in: 2025
Editore: Association for Computational Linguistics

ACM Computing Surveys (si apre in una nuova finestra)

Autori: Branislav Pecher; Ivan Srba; Maria Bielikova
Pubblicato in: ACM Computing Surveys, 2024, ISSN 0360-0300
Editore: Association for Computing Machinary, Inc.
DOI: 10.48550/ARXIV.2312.01082

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