7 papers · 1 filter
MUTANT: A Recipe for Multilingual Tokenizer Design
Souvik Rana, Arul Menezes, Ashish Kulkarni +2
Tokenizers play a crucial role in determining the performance, training efficiency, and the inference cost of Large Language Models (LLMs). Designing effective tokenizers for multi…
Chitrakshara: A Large Multilingual Multimodal Dataset for Indian languages
Shaharukh Khan, Ali Faraz, Abhinav Ravi +6
Multimodal research has predominantly focused on single-image reasoning, with limited exploration of multi-image scenarios. Recent models have sought to enhance multi-image underst…
BhashaKritika: Building Synthetic Pretraining Data at Scale for Indic Languages
Guduru Manoj, Neel Prabhanjan Rachamalla, Ashish Kulkarni +8
In the context of pretraining of Large Language Models (LLMs), synthetic data has emerged as an alternative for generating high-quality pretraining data at scale. This is particula…
Pragyaan: Designing and Curating High-Quality Cultural Post-Training Datasets for Indian Languages
Neel Prabhanjan Rachamalla, Aravind Konakalla, Gautam Rajeev +3
The effectiveness of Large Language Models (LLMs) depends heavily on the availability of high-quality post-training data, particularly instruction-tuning and preference-based examp…
Krutrim LLM: A Novel Tokenization Strategy for Multilingual Indic Languages with Petabyte-Scale Data Processing
Rahul Kumar, Shubham Kakde, Divyansh Rajput +6
We present a novel approach to data preparation for developing multilingual Indic large language model. Our meticulous data acquisition spans open-source and proprietary sources, i…
Chitranuvad: Adapting Multi-Lingual LLMs for Multimodal Translation
Shaharukh Khan, Ayush Tarun, Ali Faraz +7
In this work, we provide the system description of our submission as part of the English to Lowres Multimodal Translation Task at the Workshop on Asian Translation (WAT2024). We in…