| {"paper_url": "https://huggingface.co/papers/2309.10668", "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* [Approximating Human-Like Few-shot Learning with GPT-based Compression](https://huggingface.co/papers/2308.06942) (2023)\n* [MEMORY-VQ: Compression for Tractable Internet-Scale Memory](https://huggingface.co/papers/2308.14903) (2023)\n* [Headless Language Models: Learning without Predicting with Contrastive Weight Tying](https://huggingface.co/papers/2309.08351) (2023)\n* [Frustratingly Simple Memory Efficiency for Pre-trained Language Models via Dynamic Embedding Pruning](https://huggingface.co/papers/2309.08708) (2023)\n* [The Languini Kitchen: Enabling Language Modelling Research at Different Scales of Compute](https://huggingface.co/papers/2309.11197) (2023)\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"} |