Papers by Alexandra Dragomir

1 papers
CLewR: Curriculum Learning with Restarts for Machine Translation Preference Learning (2026.findings-acl)

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Challenge: Large language models (LLMs) have demonstrated competitive performance in zero-shot multilingual machine translation (MT).
Approach: They propose a curriculum learning strategy with restarts which reiterates easy-to-hard curriculum multiple times during training to effectively mitigate catastrophic forgetting of easy examples.
Outcome: The proposed model replicates easy-to-hard curriculum multiple times during training to mitigate catastrophic forgetting of easy examples.

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