paper-recommendations-v2 / data /2211.00635.json
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{"paper_url": "https://huggingface.co/papers/2211.00635", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Unveiling the Generalization Power of Fine-Tuned Large Language Models](https://huggingface.co/papers/2403.09162) (2024)\n* [Multitask Multilingual Model Adaptation with Featurized Low-Rank Mixtures](https://huggingface.co/papers/2402.17934) (2024)\n* [Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation](https://huggingface.co/papers/2402.18334) (2024)\n* [PEMT: Multi-Task Correlation Guided Mixture-of-Experts Enables Parameter-Efficient Transfer Learning](https://huggingface.co/papers/2402.15082) (2024)\n* [Fine-tuning Large Language Models for Domain-specific Machine Translation](https://huggingface.co/papers/2402.15061) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}