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20242026
most citedSovereign Large Language Models: Advantages, Strategy and Regulations

2 citations · 2 across the 5 of their papers we have counts for

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cs.CL2026

Last Translation Benchmark

Vilém Zouhar, Niyati Bafna, Mukund Choudhary +241

For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…

cs.CL2025

BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Data

Jaap Jumelet, Abdellah Fourtassi, Akari Haga +23

We present BabyBabelLM, a multilingual collection of datasets modeling the language a person observes from birth until they acquire a native language. We curate developmentally pla…

cs.CL2024

Benchmarking Multimodal Models for Ukrainian Language Understanding Across Academic and Cultural Domains

Yurii Paniv, Artur Kiulian, Dmytro Chaplynskyi +4

While the evaluation of multimodal English-centric models is an active area of research with numerous benchmarks, there is a profound lack of benchmarks or evaluation suites for lo…

cs.CL2024

Unsupervised Data Validation Methods for Efficient Model Training

Yurii Paniv

This paper investigates the challenges and potential solutions for improving machine learning systems for low-resource languages. State-of-the-art models in natural language proces…

cs.CL2024

Setting up the Data Printer with Improved English to Ukrainian Machine Translation

Yurii Paniv, Dmytro Chaplynskyi, Nikita Trynus +1

To build large language models for Ukrainian we need to expand our corpora with large amounts of new algorithmic tasks expressed in natural language. Examples of task performance e…