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20242026
most citedMultilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study

1 citations · 2 across the 3 of their papers we have counts for

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5 papers

cs.SE20261 cited

The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes

Redacted by arXiv

This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd conte…

cs.CL2025

Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation

Song Wang, Zihan Chen, Peng Wang +5

Retrieval-augmented generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources to address their limitations in accessing up-to-date or special…

cs.CL2025

ZeroSumEval: An Extensible Framework For Scaling LLM Evaluation with Inter-Model Competition

Hisham A. Alyahya, Haidar Khan, Yazeed Alnumay +2

We introduce ZeroSumEval, a dynamic, competition-based, and evolving evaluation framework for Large Language Models (LLMs) that leverages competitive games. ZeroSumEval encompasses…

cs.CL20251 cited

Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study

Menglong Cui, Pengzhi Gao, Wei Liu +2

Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…

cs.CL2024

LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch

Jan Pfister, Julia Wunderle, Andreas Hotho

We create two German-only decoder models, LLäMmlein 120M and 1B, transparently from scratch and publish them, along with the training data, for the German NLP research community to…