An MBZUAI team won the best paper award at the inaugural Arabic Natural Language Processing Conference for their work on processing Arabic speech. Their study establishes a new approach to tackle the complexities of spoken Arabic, which differs significantly from text-based language models. The team's approach aims to advance new tools for Arabic speakers by addressing challenges like intonation and the continuous nature of speech. Why it matters: This award highlights the importance of specialized research in Arabic NLP, as mainstream LLMs often face limitations in accurately processing the nuances of Arabic speech.
MBZUAI faculty won two awards and published eight papers at the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL 2023). Alham Fikri Aji and Fajri Koto won the Best Resource Award for NusaWrites, a paper on constructing high-quality corpora for low-resource Indonesian languages by engaging speaker communities. Muhammad Abdul-Mageed won an Area Chair award for ProMap, a method for constructing bilingual dictionaries via language model prompting. Why it matters: This highlights MBZUAI's contribution to NLP research, particularly in low-resource languages and bilingual lexicon induction, and strengthens its position as a hub for AI research in the region.
NYUAD and MBZUAI co-hosted the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP) in Abu Dhabi from December 7-11. EMNLP is a top-tier NLP and AI conference organized by the ACL special interest group on linguistic data (SIGDAT). MBZUAI's Natural Language Processing Department is actively developing NLP datasets and methods to solve social problems. Why it matters: Hosting EMNLP in the UAE highlights the growing importance of NLP research in the region and the increasing contributions of local institutions like MBZUAI to the field.
MBZUAI faculty and students will present 44 papers at the Empirical Methods in Natural Language Processing (EMNLP) conference in Singapore. Research topics include disinformation detection, social media analysis, dialogue generation, and Arabic LLMs. Preslav Nakov, Iryna Gurevych, Timothy Baldwin, Alham Fikri Aji, and Muhammad Abdul-Mageed are among the MBZUAI researchers presenting at the conference. Why it matters: MBZUAI's strong presence at a top NLP conference highlights the UAE's growing contributions to cutting-edge AI research and its increasing global prominence in the field.
A study co-authored by researchers from UC Berkeley, University of the Witwatersrand, Lelapa AI, and MBZUAI received the Outstanding Paper Award at EMNLP 2024. The paper critiques the term "low-resource" languages in NLP, highlighting its limitations in capturing the diverse challenges faced by different languages. The authors propose a more detailed analysis of resourcedness to encourage targeted support for languages currently underserved by technology. Why it matters: The research challenges assumptions in NLP and promotes more nuanced approaches to supporting the world's many languages, including Arabic, in AI systems.