{"id":293089,"date":"2024-12-03T17:19:23","date_gmt":"2024-12-03T17:19:23","guid":{"rendered":"https:\/\/staging-artefact.digitalseeder.com\/?post_type=blog&p=293089"},"modified":"2024-12-03T17:20:10","modified_gmt":"2024-12-03T17:20:10","slug":"is-preference-alignment-always-the-best-option-to-enhance-llm-based-translation-an-empirical-analysis","status":"publish","type":"blog","link":"https:\/\/staging-artefact.digitalseeder.com\/fr\/blog\/is-preference-alignment-always-the-best-option-to-enhance-llm-based-translation-an-empirical-analysis\/","title":{"rendered":"L'alignement des pr\u00e9f\u00e9rences est-il toujours la meilleure option pour am\u00e9liorer la traduction bas\u00e9e sur les grands mod\u00e8les linguistiques ? Une analyse empirique"},"content":{"rendered":"

Hippolyte Gisserot-Boukhlef, Ricardo Rei, Emmanuel Malherbe, C\u00e9line Hudelot, Pierre Colombo, Nuno M. Guerreiro<\/p>\n

Artefact Research Center, Unbabel, Equall, MICS CentraleSup\u00e9lec, Universit\u00e9 Paris-Saclay, Instituto de Telecomunica\u00e7\u00f5es, Instituto Superior T\u00e9cnico & Universidade de Lisboa (Lisbon ELLIS Unit)<\/p>\n<\/div><\/div><\/div><\/div><\/div>

Read the Article <\/span><\/a><\/div>

We are pleased to share the latest research article by our PhD student, Hippolyte Gisserot-Boukhlef, which has been selected as a featured paper at the Ninth Conference on Machine Translation (WMT24) in November 2024.<\/p>\n<\/div>

Abstract<\/h2><\/div>

The paper explores the effectiveness of Preference Optimization techniques, particularly in comparison to Supervised Fine-Tuning. While optimizing on preference data is a common practice in machine translation\u2014often leveraging high-quality outputs from external models like GPT-4\u2014the broader implications of this approach are not yet fully understood. Interestingly, our findings suggest that using the model itself as a self-teacher can achieve comparable translation quality, while eliminating the complexities and constraints associated with relying on external systems.<\/p>\n<\/div>

Access the slide Deck <\/span><\/a><\/div><\/div><\/div><\/div><\/article><\/p>","protected":false},"excerpt":{"rendered":"

Les m\u00e9triques neuronales pour l'\u00e9valuation de la traduction automatique (TA) sont devenues de plus en plus importantes en raison de leur meilleure corr\u00e9lation avec les jugements humains par rapport aux m\u00e9triques lexicales traditionnelles.<\/p>","protected":false},"featured_media":293097,"parent":0,"template":"","meta":{"_acf_changed":false},"blog-category":[21939],"blog-language":[2991,2993],"class_list":["post-293089","blog","type-blog","status-publish","has-post-thumbnail","hentry","blog-category-medium","blog-language-en","blog-language-fr"],"acf":[],"yoast_head":"\nIs Preference Alignment Always the Best Option to Enhance LLM-Based Translation? 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