The Fine-Tuning Paradox: Boosting Translation Quality Without
Sacrificing LLM Abilities

The Fine-Tuning Paradox: Boosting Translation Quality Without Sacrificing LLM Abilities

30 May 2024

Christof Monz

Papers citing "The Fine-Tuning Paradox: Boosting Translation Quality Without Sacrificing LLM Abilities"

6 / 6 papers shown

Title
Beyond Decoder-only: Large Language Models Can be Good Encoders for Machine Translation Yingfeng Luo Tong Zheng Yongyu Mu B. Li Qinghong Zhang ... Ziqiang Xu Peinan Feng Xiaoqian Liu Tong Xiao Jingbo Zhu AI4CE 70 0 0 09 Mar 2025
The Falcon Series of Open Language Models Ebtesam Almazrouei Hamza Alobeidli Abdulaziz Alshamsi Alessandro Cappelli Ruxandra-Aimée Cojocaru ... Quentin Malartic Daniele Mazzotta Badreddine Noune B. Pannier Guilherme Penedo AI4TS ALM 113 389 0 28 Nov 2023
Identifying Context-Dependent Translations for Evaluation Set Production R. Wicks Matt Post 24 11 0 04 Nov 2023
Steering Large Language Models for Machine Translation with Finetuning and In-Context Learning Duarte M. Alves Nuno M. Guerreiro Joao Alves José P. Pombal Ricardo Rei José G. C. de Souza Pierre Colombo André F.T. Martins 45 47 0 20 Oct 2023
CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task Ricardo Rei Marcos Vinícius Treviso Nuno M. Guerreiro Chrysoula Zerva Ana C. Farinha ... T. Glushkova Duarte M. Alves A. Lavie Luísa Coheur André F. T. Martins 52 137 0 13 Sep 2022
Controlling Translation Formality Using Pre-trained Multilingual Language Models Elijah Matthew Rippeth Sweta Agrawal Marine Carpuat AI4CE 42 15 0 13 May 2022