We introduce Latxa, a family of large language models for Basque ranging from 7 to 70
billion parameters. Latxa is based on Llama 2, which we continue pretraining on a new …

Large Language Models (LLMs) have gained significant attention due to their high
performance on a wide range of natural language tasks since the release of ChatGPT. The …

Large language models (LLMs) have demonstrated significant progress in various natural
language generation and understanding tasks. However, their linguistic generalization …

ELOQUENT is a set of shared tasks for evaluating the quality and usefulness of generative
language models. ELOQUENT aims to apply high-level quality criteria, grounded in …

Recent advances in Large Language Models (LLMs) have revolutionized code generation,
leading to widespread adoption of AI coding tools by developers. However, LLMs can …

The advancement of large language models (LLMs) has predominantly focused on high-
resource languages, leaving low-resource languages, such as those in the Finno-Ugric …

Optical Character Recognition (OCR) systems often introduce errors when transcribing
historical documents, leaving room for post-correction to improve text quality. This study …

We introduce GECKO, a bilingual large language model (LLM) optimized for Korean and
English, along with programming languages. GECKO is pretrained on the balanced, high …

Traffic insurance law can be a complex domain for ordinary individuals to grasp, thus
affecting its accessibility. Although the traffic insurance law itself and precedents are publicly …

In this Thesis we consider Code World Models, world models generated by a Large
Language Model (LLM) in the form of Python code for offline model-based Reinforcement …