| William, To understand what they are doing, at a minimum you have to know calculus, linear algebra, and a computer language. John M. de Figueiredo Sent from my iPhone Send some clarification on the entire project. WRDS
Konkani LLM: Multi-Script Instruction Tuning and Evaluation for a Low-Resource Indian Language
Large Language Models (LLMs) consistently under perform in
low-resource linguistic contexts such as Konkani. This performance
deficit stems from acute training data scarcity compounded by high
script diversity across Devanagari, Romi and Kannada orthographies. To
address this gap, we introduce Konkani-Instruct-100k, a comprehensive
synthetic instruction-tuning dataset generated through Gemini 3.
We establish rigorous baseline benchmarks by evaluating leading
open-weights architectures including Llama 3.1, Qwen2.5 and Gemma 3
alongside proprietary closed-source models. Our primary contribution
involves the development of Konkani LLM, a series of fine-tuned models
optimized for regional nuances. Furthermore, we are developing the
Multi-Script Konkani Benchmark to facilitate cross-script linguistic
evaluation. In machine translation, Konkani LLM delivers consistent
gains over the corresponding base models and is competitive with and in
several settings surpasses proprietary baselines https://arxiv.org/abs/2603.23529
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