2 papers
cs.CL2025
Data-Efficient Domain Adaptation for LLM-based MT using Contrastive Preference Optimization
Inacio Vieira, Antonio Castaldo, James O'Doherty +1
LLMs often require adaptation to domain-specific requirements, a process that can be expensive when relying solely on SFT. We present an empirical study on applying CPO to simulate…
cs.CL2025
Extending CREAMT: Leveraging Large Language Models for Literary Translation Post-Editing
Antonio Castaldo, Sheila Castilho, Joss Moorkens +1
Post-editing machine translation (MT) for creative texts, such as literature, requires balancing efficiency with the preservation of creativity and style. While neural MT systems s…