{"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\/de\/blog\/is-preference-alignment-always-the-best-option-to-enhance-llm-based-translation-an-empirical-analysis\/","title":{"rendered":"Ist Preference Alignment immer die beste Option zur Verbesserung von LLM-basierten \u00dcbersetzungen? Eine empirische Analyse"},"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":"

Neuronale Metriken f\u00fcr die maschinelle \u00dcbersetzung (MT) zur Evaluierung sind aufgrund ihrer \u00fcberlegenen Korrelation mit menschlichen Urteilen im Vergleich zu traditionellen lexikalischen Metriken immer prominenter geworden.<\/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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