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20232026
most citedTokenizer Choice For LLM Training: Negligible or Crucial?

4 citations · 10 across the 10 of their papers we have counts for

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Showing 2024 · cs.CLShow all

5 papers · 2 filters

cs.CL2024★ 3 cited

Towards Multilingual LLM Evaluation for European Languages

Klaudia Thellmann, Bernhard Stadler, Michael Fromm +8

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…

cs.CL2024

Data Processing for the OpenGPT-X Model Family

Nicolo' Brandizzi, Hammam Abdelwahab, Anirban Bhowmick +19

This paper presents a comprehensive overview of the data preparation pipeline developed for the OpenGPT-X project, a large-scale initiative aimed at creating open and high-performa…

cs.CL2024★ 2 cited

Teuken-7B-Base & Teuken-7B-Instruct: Towards European LLMs

Mehdi Ali, Michael Fromm, Klaudia Thellmann +38

We present two multilingual LLMs, Teuken 7B-base and Teuken 7B-instruct, designed to embrace Europe's linguistic diversity by supporting all 24 official languages of the European U…

cs.CL2024

Do Multilingual Large Language Models Mitigate Stereotype Bias?

Shangrui Nie, Michael Fromm, Charles Welch +7

While preliminary findings indicate that multilingual LLMs exhibit reduced bias compared to monolingual ones, a comprehensive understanding of the effect of multilingual training o…

cs.CL2024

Investigating Multilingual Instruction-Tuning: Do Polyglot Models Demand for Multilingual Instructions?

Alexander Arno Weber, Klaudia Thellmann, Jan Ebert +4

The adaption of multilingual pre-trained LLMs into eloquent and helpful assistants is essential to facilitate their use across different language regions. In that spirit, we are th…