data/2211.12677.json

{"paper_url": "https://huggingface.co/papers/2211.12677", "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* [Integrating Multi-scale Contextualized Information for Byte-based Neural Machine Translation](https://huggingface.co/papers/2405.19290) (2024)\n* [MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization](https://huggingface.co/papers/2407.08818) (2024)\n* [T-FREE: Tokenizer-Free Generative LLMs via Sparse Representations for Memory-Efficient Embeddings](https://huggingface.co/papers/2406.19223) (2024)\n* [Super Tiny Language Models](https://huggingface.co/papers/2405.14159) (2024)\n* [Investigating the translation capabilities of Large Language Models trained on parallel data only](https://huggingface.co/papers/2406.09140) (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`"}