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20212026
most citedFast Yet Effective Machine Unlearning

176 citations · 360 across the 13 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025★ 1 cited

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)…

cs.CL2025

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…

cs.AI2025

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…