1 citations · 1 across the 6 of their papers we have counts for
3 papers · 1 filter
Alif: Advancing Urdu Large Language Models via Multilingual Synthetic Data Distillation
Muhammad Ali Shafique, Kanwal Mehreen, Muhammad Arham +3
Developing a high-performing large language models (LLMs) for low-resource languages such as Urdu, present several challenges. These challenges include the scarcity of high-quality…
Query Attribute Modeling: Improving search relevance with Semantic Search and Meta Data Filtering
Karthik Menon, Batool Arhamna Haider, Muhammad Arham +3
This study introduces Query Attribute Modeling (QAM), a hybrid framework that enhances search precision and relevance by decomposing open text queries into structured metadata tags…
Improving Multilingual Capabilities with Cultural and Local Knowledge in Large Language Models While Enhancing Native Performance
Ram Mohan Rao Kadiyala, Siddartha Pullakhandam, Siddhant Gupta +6
Large Language Models (LLMs) have shown remarkable capabilities, but their development has primarily focused on English and other high-resource languages, leaving many languages un…