Papers by Mudit Somani
Continual-learning for Modelling Low-Resource Languages from Large Language Models (2026.eacl-long)
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| Challenge: | Existing models for low-resource languages with catastrophic forgetting pose several challenges, including learning to model multi-lingual scenarios. |
| Approach: | They propose to employ a continual learning strategy using parts-of-speech code-switching and replay adapter strategies to mitigate catastrophic forgetting gap while training LLM from LLM. |
| Outcome: | The proposed architecture is able to train LLMs from LLM and mitigate catastrophic forgetting gap on vision language tasks. |