9 papers
inLoRA-MINT: Internal Representations for Auditing Training Data in Domain-adapted LLMs
Gonzalo Mancera, Julian Fierrez, Aythami Morales +3
This work investigates the application of the Membership Inference Test (MINT) to large language models (LLMs) fine-tuned with LoRA, aiming to determine whether specific samples we…
AIriskEval-edu Demo: Auditing of Pedagogical Risks in Educational Explanations
Javier Irigoyen, Roberto Daza, Francisco Jurado +5
We present AIriskEval-edu Demo, a platform that audits the pedagogical quality of instructional explanations and provides explainable audit results. The platform evaluates an expla…
CrimeNER Demo: Named-Entity Recognition in the Crime Domain
Miguel Lopez-Duran, Julian Fierrez, Aythami Morales +7
We present CrimeNER Demo, an AI-powered platform that enables us to extract general crime-related information from documents and classify them into entity types with two levels of…
Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyond
Javier Irigoyen, Roberto Daza, Aythami Morales +5
The society and emerging risk-based regulatory frameworks for AI underscore the need for rigorous risk assessment to ensure safe and reliable AI systems. In response to this impera…
AIriskEval-edu: New Dataset for Risk Assessment in AI-mediated K-12 Educational Explanations
Javier Irigoyen, Roberto Daza, Francisco Jurado +5
This work introduces AIriskEval-edu-db2, a new dataset designed to train and evaluate auditors based on LLMs for an explainable pedagogical risk assessment in instructional content…
Auditing Training Data in Domain-adapted LLMs: LoRA-MINT
Gonzalo Mancera, Daniel DeAlcala, Aythami Morales +3
We present LoRA-MINT, a new methodology for Membership Inference Test (MINT) applied to recent Large Language Models (LLMs) fine-tuned for specific Natural Language Processing (NLP…
CrimeNER: Curated Dataset and Methods for Research and Investigation in Language Intelligence
Miguel Lopez-Duran, Julian Fierrez, Aythami Morales +7
The extraction of critical information from crime-related documents is a crucial task for law enforcement agencies. The extraction of this information can be interpreted as a Named…
EduEVAL-DB: A Role-Based Dataset for Pedagogical Risk Evaluation in Educational Explanations
Javier Irigoyen, Roberto Daza, Aythami Morales +4
This work introduces EduEVAL-DB, a dataset based on teacher roles designed to support the evaluation and training of automatic pedagogical evaluators and AI tutors for instructiona…
PBa-LLM: Privacy- and Bias-aware NLP using Named-Entity Recognition (NER)
Gonzalo Mancera, Aythami Morales, Julian Fierrez +5
The use of Natural Language Processing (NLP) in highstakes AI-based applications has increased significantly in recent years, especially since the emergence of Large Language Model…