  We describe the findings of the fourth Nuanced Arabic Dialect Identification
Shared Task (NADI 2023). The objective of NADI is to help advance
state-of-the-art Arabic NLP by creating opportunities for teams of researchers
to collaboratively compete under standardized conditions. It does so with a
focus on Arabic dialects, offering novel datasets and defining subtasks that
allow for meaningful comparisons between different approaches. NADI 2023
targeted both dialect identification (Subtask 1) and dialect-to-MSA machine
translation (Subtask 2 and Subtask 3). A total of 58 unique teams registered
for the shared task, of whom 18 teams have participated (with 76 valid
submissions during test phase). Among these, 16 teams participated in Subtask
1, 5 participated in Subtask 2, and 3 participated in Subtask 3. The winning
teams achieved 87.27
  F1 on Subtask 1, 14.76 Bleu in Subtask 2, and 21.10 Bleu in Subtask 3,
respectively. Results show that all three subtasks remain challenging, thereby
motivating future work in this area. We describe the methods employed by the
participating teams and briefly offer an outlook for NADI.
