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Large language models are powerful but often limited by high computational cost, privacy concerns, and English-centric training. Recent progress demonstrates that small, efficient models with around one billion parameters can deliver strong…

Computation and Language · Computer Science 2025-12-16 Anna Aksenova , Boris Zverkov , Nicola Dainese , Alexander Nikitin , Pekka Marttinen

Large language models (LLMs) demonstrate unprecedented capabilities and define the state of the art for almost all natural language processing (NLP) tasks and also for essentially all Language Technology (LT) applications. LLMs can only be…

Computation and Language · Computer Science 2025-02-19 Georg Rehm , Annika Grützner-Zahn , Fabio Barth

Despite recent advances in multimodal large language models (MLLMs), their development has predominantly focused on English- and western-centric datasets and tasks, leaving most of the world's languages and diverse cultural contexts…

Current large language models (LLMs) are trained on massive amounts of text data, primarily from a few dominant languages. Studies suggest that this over-reliance on high-resource languages, such as English, hampers LLM performance in mid-…

Computation and Language · Computer Science 2025-12-12 Iñaki Lacunza , José Javier Saiz , Alexander Shvets , Aitor Gonzalez-Agirre , Marta Villegas

The quality of open-weight LLMs has seen significant improvement, yet they remain predominantly focused on English. In this paper, we introduce the EuroLLM project, aimed at developing a suite of open-weight multilingual LLMs capable of…

The rise of Large Language Models (LLMs) has revolutionized natural language processing across numerous languages and tasks. However, evaluating LLM performance in a consistent and meaningful way across multiple European languages remains…

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by…

Computation and Language · Computer Science 2023-10-31 Yizhe Yang , Huashan Sun , Jiawei Li , Runheng Liu , Yinghao Li , Yuhang Liu , Heyan Huang , Yang Gao

High-resource languages such as English, enables the pretraining of high-quality large language models (LLMs). The same can not be said for most other languages as LLMs still underperform for non-English languages, likely due to a gap in…

Computation and Language · Computer Science 2025-02-20 Jiayi Wang , Yao Lu , Maurice Weber , Max Ryabinin , David Adelani , Yihong Chen , Raphael Tang , Pontus Stenetorp

The driving factors behind the development of large language models (LLMs) with impressive learning capabilities are their colossal model sizes and extensive training datasets. Along with the progress in natural language processing, LLMs…

Computation and Language · Computer Science 2023-09-19 Thuat Nguyen , Chien Van Nguyen , Viet Dac Lai , Hieu Man , Nghia Trung Ngo , Franck Dernoncourt , Ryan A. Rossi , Thien Huu Nguyen

The development of open-source, multilingual medical language models can benefit a wide, linguistically diverse audience from different regions. To promote this domain, we present contributions from the following: First, we construct a…

Computation and Language · Computer Science 2024-06-04 Pengcheng Qiu , Chaoyi Wu , Xiaoman Zhang , Weixiong Lin , Haicheng Wang , Ya Zhang , Yanfeng Wang , Weidi Xie

Large language models (LLMs) demonstrate remarkable ability to comprehend, reason, and generate following nature language instructions. However, the development of LLMs has been primarily focused on high-resource languages, such as English,…

Large language models (LLMs) offer promise in generating educational content, providing instructor feedback, and reducing teacher workload on assessments. While prior studies have focused on studying LLM-powered learning analytics, limited…

Computation and Language · Computer Science 2024-11-08 Anand Syamkumar , Nora Tseng , Kaycie Barron , Shanglin Yang , Shamya Karumbaiah , Rheeya Uppal , Junjie Hu

Large language models (LLMs) have become integral to a wide range of applications worldwide, driving an unprecedented global demand for effective multilingual capabilities. Central to achieving robust multilingual performance is the…

Computation and Language · Computer Science 2025-09-22 Ping Guo , Yubing Ren , Binbin Liu , Fengze Liu , Haobin Lin , Yifan Zhang , Bingni Zhang , Taifeng Wang , Yin Zheng

English, as a very high-resource language, enables the pretraining of high-quality large language models (LLMs). The same cannot be said for most other languages, as leading LLMs still underperform for non-English languages, likely due to a…

Computation and Language · Computer Science 2024-11-07 Jiayi Wang , Yao Lu , Maurice Weber , Max Ryabinin , Yihong Chen , Raphael Tang , Pontus Stenetorp

Continued pretraining and instruction tuning on large-scale multilingual data have proven to be effective in scaling large language models (LLMs) to low-resource languages. However, the unaligned nature of such data limits its ability to…

Computation and Language · Computer Science 2025-10-22 Yingli Shen , Wen Lai , Shuo Wang , Ge Gao , Kangyang Luo , Alexander Fraser , Maosong Sun

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 LLMs learn to understand and generate language by training billions of…

Computation and Language · Computer Science 2024-08-29 Wazir Ali , Sampo Pyysalo

The breakthrough of generative large language models (LLMs) that can solve different tasks through chat interaction has led to a significant increase in the use of general benchmarks to assess the quality or performance of these models…

Computation and Language · Computer Science 2025-04-03 Fabio Barth , Georg Rehm

Open large language models (LLMs) have demonstrated improving multilingual capabilities in recent years. In this paper, we present a study of open LLMs for multilingual machine translation (MT) across a range of languages, and investigate…

Computation and Language · Computer Science 2026-02-26 Yuzhe Shang , Pengzhi Gao , Wei Liu , Jian Luan , Jinsong Su
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