Search Results for author:
Found 10 papers, 5 papers with code
Pitfalls of Conversational LLMs on News Debiasing
This paper addresses debiasing in news editing and evaluates the effectiveness of conversational Large Language Models in this task.
Spot: A Natural Language Interface for Geospatial Searches in OSM
Investigative journalists and fact-checkers have found OpenStreetMap (OSM) to be an invaluable resource for their work due to its extensive coverage and intricate details of various locations, which play a crucial role in investigating news scenes.
DWReCO at CheckThat! 2023: Enhancing Subjectivity Detection through Style-based Data Sampling
This paper describes our submission for the subjectivity detection task at the CheckThat!
Multilingual Detection of Check-Worthy Claims using World Languages and Adapter Fusion
This paper proposes cross-training adapters on a subset of world languages, combined by adapter fusion, to detect claims emerging globally in multiple languages.
UPV at TREC Health Misinformation Track 2021 Ranking with SBERT and Quality Estimators
Health misinformation on search engines is a significant problem that could negatively affect individuals or public health.
Sexism Prediction in Spanish and English Tweets Using Monolingual and Multilingual BERT and Ensemble Models
This work obtained first place in both tasks at EXIST, with the highest accuracies (0. 780 for task 1 and 0. 658 for task 2) and F1-scores (F1-binary of 0. 780 for task 1 and F1-macro of 0. 579 for task 2).
AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models
The shared task is divided into two related classification tasks: (i) Task 1: toxicity detection and; (ii) Task 2: toxicity level detection.
UPV at CheckThat! 2021: Mitigating Cultural Differences for Identifying Multilingual Check-worthy Claims
Identifying check-worthy claims is often the first step of automated fact-checking systems.
Unified and Multilingual Author Profiling for Detecting Haters
This paper presents a unified user profiling framework to identify hate speech spreaders by processing their tweets regardless of the language.
Leveraging Commonsense Knowledge on Classifying False News and Determining Checkworthiness of Claims
In this paper, we propose to leverage commonsense knowledge for the tasks of false news classification and check-worthy claim detection.
