Code-mixing is considered as a linguistic phenomenon that combines several languages into one text. It has now become very common in multilingual societies, especially in digital communication. Word-Level Identification of Languages in Dravidian Languages (WILD) - a Code-mixed Language Identification (CoLI) in Dravidian languages shared task, organized as a part of Forum for Information Retrieval and Evaluation (FIRE) 2025, put forward these challenges to the researchers by asking them to develop models capable of classifying words in code-mixed texts involving Dravidian languages - Tamil, Telugu, Malayalam, Kannada, and Tulu, which are interwoven with English. It poses significant challenges due to the complexity of linguistic structures, mixed-language tokens, and dialectal variations in low-resource languages such as those from the Dravidian family. The participating teams used different methodologies, ranging from traditional Machine Learning (ML) to Deep Learning and transformer-based models to address these challenges. This paper presents the important findings of the task and an overview of the submitted methodologies.
