Robert Farrell, Rajarshi Das, et al.
AAAI-SS 2010
This paper presents the approach of the NLPeople team to the Nuanced Arabic Dialect Identification (NADI) 2023 shared task. Subtask 1 involves identifying the dialect of a source text at the country level. Our approach to Subtask 1 makes use of language-specific language models, a clustering and retrieval method to provide additional context to a target sentence, a fine-tuning strategy which makes use of the provided data from the 2020 and 2021 shared tasks, and finally, ensembling over the predictions of multiple models. Our submission achieves a macro-averaged F1 score of 87.27, ranking 1st among the other participants in the task.
Robert Farrell, Rajarshi Das, et al.
AAAI-SS 2010
Takuma Udagawa, Aashka Trivedi, et al.
EMNLP 2023
Chen-chia Chang, Wan-hsuan Lin, et al.
ICML 2025
Gang Liu, Michael Sun, et al.
ICLR 2025