Papers by Mohammad Amin Ghanizadeh
Dynamic Jointly Batch Selection for Data Efficient Machine Translation Fine-Tuning (2025.emnlp-main)
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| Challenge: | Data quality and effective selection are key to improving machine translation performance . study focuses on fine-tuning models using a batch selection strategy . |
| Approach: | They propose a data selection methodology for fine-tuning machine translation systems that leverages the synergy between a learner model and a pre-trained reference model to enhance overall training effectiveness. |
| Outcome: | The proposed method improves training efficiency by up to fivefold compared to baseline methods. |