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HausaNLP at SemEval-2023 Task 10: Transfer Learning, Synthetic Data and Side-Information for Multi-Level Sexism Classification

2023-04-28 · Saminu Mohammad Aliyu, Idris Abdulmumin, Shamsuddeen Hassan Muhammad, Ibrahim Said Ahmad, Saheed Abdullahi Salahudeen, Aliyu Yusuf, Falalu Ibrahim Lawan

We present the findings of our participation in the SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS) task, a shared task on offensive language (sexism) detection on English Gab and Reddit dataset. We investigated the effects of transferring two language models: XLM-T (sentiment classification) and HateBERT (same domain -- Reddit) for multi-level classification into Sexist or not Sexist, and other subsequent sub-classifications of the sexist data. We also use synthetic classification of unlabelled dataset and intermediary class information to maximize the performance of our models. We submitted a system in Task A, and it ranked 49th with F1-score of 0.82. This result showed to be competitive as it only under-performed the best system by 0.052% F1-score.

📄 PDF Abstract BibTeX arXiv:2305.00076

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Tasks

Classification Sentiment AnalysisSentiment ClassificationTransfer Learning

HausaNLP at SemEval-2025 Task 2: Entity-Aware Fine-tuning vs. Prompt Engineering in Entity-Aware Machine Translation

2025-03-25 · Abdulhamid Abubakar, Hamidatu Abdulkadir, Ibrahim Rabiu Abdullahi, Abubakar Auwal Khalid 외

This paper presents our findings for SemEval 2025 Task 2, a shared task on entity-aware machine translation (EA-MT). The goal of this task is to develop translation models that can accurately translate English sentences …

Machine Translation Prompt Engineering Task 2 Translation

HausaNLP at SemEval-2025 Task 3: Towards a Fine-Grained Model-Aware Hallucination Detection

2025-03-25 · Maryam Bala, Amina Imam Abubakar, Abdulhamid Abubakar, Abdulkadir Shehu Bichi 외

This paper presents our findings of the Multilingual Shared Task on Hallucinations and Related Observable Overgeneration Mistakes, MU-SHROOM, which focuses on identifying hallucinations and related overgeneration errors …

Hallucination Natural Language Inference

HausaNLP at SemEval-2023 Task 12: Leveraging African Low Resource TweetData for Sentiment Analysis

2023-04-26 · Saheed Abdullahi Salahudeen, Falalu Ibrahim Lawan, Ahmad Mustapha Wali, Amina Abubakar Imam 외

We present the findings of SemEval-2023 Task 12, a shared task on sentiment analysis for low-resource African languages using Twitter dataset. The task featured three subtasks; subtask A is monolingual sentiment classifi…

Sentiment Analysis Sentiment Classification Twitter Sentiment Analysis Zero-shot Sentiment Classification

HausaNLP: Current Status, Challenges and Future Directions for Hausa Natural Language Processing

2025-05-20 · Shamsuddeen Hassan Muhammad, Ibrahim Said Ahmad, Idris Abdulmumin, Falalu Ibrahim Lawan 외

Hausa Natural Language Processing (NLP) has gained increasing attention in recent years, yet remains understudied as a low-resource language despite having over 120 million first-language (L1) and 80 million second-langu…

Language Modeling Language Modelling Machine Translation Multilingual NLP+7

DMCB at SemEval-2018 Task 1: Transfer Learning of Sentiment Classification Using Group LSTM for Emotion Intensity prediction

2018-06-01 · SEMEVAL 2018 6 · Youngmin Kim, Hyunju Lee

This paper describes a system attended in the SemEval-2018 Task 1 {``}Affect in tweets{''} that predicts emotional intensities. We use Group LSTM with an attention model and transfer learning with sentiment classificatio…

General Classification regression Sentiment Analysis Sentiment Classification+2