Detecting Misinformation with LLM-Predicted Credibility Signals and Weak Supervision

no code implementations • 14 Sep 2023 • João A. Leite, Olesya Razuvayevskaya, Kalina Bontcheva, Carolina Scarton

Credibility signals represent a wide range of heuristics that are typically used by journalists and fact-checkers to assess the veracity of online content.

Misinformation

Noisy Self-Training with Data Augmentations for Offensive and Hate Speech Detection Tasks

1 code implementation • 31 Jul 2023 • João A. Leite, Carolina Scarton, Diego F. Silva

Online social media is rife with offensive and hateful comments, prompting the need for their automatic detection given the sheer amount of posts created every second.

Data Augmentation Hate Speech Detection

SheffieldVeraAI at SemEval-2023 Task 3: Mono and multilingual approaches for news genre, topic and persuasion technique classification

no code implementations • 16 Mar 2023 • Ben Wu, Olesya Razuvayevskaya, Freddy Heppell, João A. Leite, Carolina Scarton, Kalina Bontcheva, Xingyi Song

For Subtask 2 (Framing), we achieved first place in 3 languages, and the best average rank across all the languages, by using two separate ensembles: a monolingual RoBERTa-MUPPETLARGE and an ensemble of XLM-RoBERTaLARGE with adapters and task adaptive pretraining.

Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis

1 code implementation • Asian Chapter of the Association for Computational Linguistics 2020 • João A. Leite, Diego F. Silva, Kalina Bontcheva, Carolina Scarton

Therefore, identifying these comments is an important task for studying and preventing the proliferation of toxicity in social media.

Hate Speech Detection Multi-Label Classification +1