Ahnaf Mozib Samin

Also published as: Ahnaf Mozib Samin


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garNER at SemEval-2023: Simplified Knowledge Augmentation for Multilingual Complex Named Entity Recognition
Md Zobaer Hossain | Averie Ho Zoen So | Silviya Silwal | H. Andres Gonzalez Gongora | Ahnaf Mozib Samin | Jahedul Alam Junaed | Aritra Mazumder | Sourav Saha | Sabiha Tahsin Soha
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)

This paper presents our solution, garNER, to the SemEval-2023 MultiConer task. We propose a knowledge augmentation approach by directly querying entities from the Wikipedia API and appending the summaries of the entities to the input sentence. These entities are either retrieved from the labeled training set (Gold Entity) or from off-the-shelf entity taggers (Entity Extractor). Ensemble methods are then applied across multiple models to get the final prediction. Our analysis shows that the added contexts are beneficial only when such contexts are relevant to the target-named entities, but detrimental when the contexts are irrelevant.

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UM-DFKI Maltese Speech Translation
Aiden Williams | Kurt Abela | Rishu Kumar | Martin Bär | Hannah Billinghurst | Kurt Micallef | Ahnaf Mozib Samin | Andrea DeMarco | Lonneke van der Plas | Claudia Borg
Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)

For the 2023 IWSLT Maltese Speech Translation Task, UM-DFKI jointly presents a cascade solution which achieves 0.6 BLEU. While this is the first time that a Maltese speech translation task has been released by IWSLT, this paper explores previous solutions for other speech translation tasks, focusing primarily on low-resource scenarios. Moreover, we present our method of fine-tuning XLS-R models for Maltese ASR using a collection of multi-lingual speech corpora as well as the fine-tuning of the mBART model for Maltese to English machine translation.


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Arguments to Key Points Mapping with Prompt-based Learning
Ahnaf Mozib Samin | Behrooz Nikandish | Jingyan Chen
Proceedings of the 5th International Conference on Natural Language and Speech Processing (ICNLSP 2022)