2 citations · 2 across the 6 of their papers we have counts for
6 papers
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…
IndicVisionBench: Benchmarking Cultural and Multilingual Understanding in VLMs
Ali Faraz, Akash, Shaharukh Khan +6
Vision-language models (VLMs) have demonstrated impressive generalization across multimodal tasks, yet most evaluation benchmarks remain Western-centric, leaving open questions abo…
Seeing Straight: Document Orientation Detection for Efficient OCR
Suranjan Goswami, Abhinav Ravi, Raja Kolla +5
Despite significant advances in document understanding, determining the correct orientation of scanned or photographed documents remains a critical pre-processing step in the real…
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…
Krutrim LLM: Multilingual Foundational Model for over a Billion People
Aditya Kallappa, Palash Kamble, Abhinav Ravi +10
India is a diverse society with unique challenges in developing AI systems, including linguistic diversity, oral traditions, data accessibility, and scalability. Existing foundatio…
Chitrarth: Bridging Vision and Language for a Billion People
Shaharukh Khan, Ayush Tarun, Abhinav Ravi +7
Recent multimodal foundation models are primarily trained on English or high resource European language data, which hinders their applicability to other medium and low-resource lan…