4 citations · 4 across the 2 of their papers we have counts for
6 papers
Revisiting Multilingual Data Mixtures in Language Model Pretraining
Negar Foroutan, Paul Teiletche, Ayush Kumar Tarun +1
The impact of different multilingual data mixtures in pretraining large language models (LLMs) has been a topic of ongoing debate, often raising concerns about potential trade-offs…
Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
Project Apertus, Alejandro Hernández-Cano, Alexander Hägele +100
We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingu…
Can Performant LLMs Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs
Dongyang Fan, Vinko Sabolčec, Matin Ansaripour +4
The increasing adoption of web crawling opt-outs by copyright holders of online content raises critical questions about the impact of data compliance on large language model (LLM)…
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…
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…
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
Angelika Romanou, Negar Foroutan, Anna Sotnikova +56
The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…