Generative vs. Encoder Models for Multilingual NER: A Comprehensive Empirical Study on Naamapadam
This paper presents a rigorous comparative study of generative and encoder-based neural architectures for NER on all eleven languages of the Naamapadam benchmark; identifies three language clusters--encoder-dominant, partial-coverage, and failure-zone; and provides actionable deployment guidelines grounded in transfer learning and low-resource NLP principles.