Papers by Marek Kadlcik
Soft Alignment Objectives for Robust Adaptation of Language Generation (2023.acl-long)
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| Challenge: | Domain adaptation is a common approach for generative language models, but it is notorious for over-specialization to the target domain, resulting in catastrophic forgetting. |
| Approach: | They propose to build training objectives on a semantic similarity of predicted tokens to the reference and avoid catastrophic forgetting of adaptation by preserving adaptation in-domain quality. |
| Outcome: | The proposed objectives mitigate catastrophic forgetting while preserving the adaptation in-domain quality while reducing computational costs. |