| {"paper_url": "https://huggingface.co/papers/2209.13569", "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* [SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining](https://huggingface.co/papers/2406.02214) (2024)\n* [LoQT: Low Rank Adapters for Quantized Training](https://huggingface.co/papers/2405.16528) (2024)\n* [Revealing the Utilized Rank of Subspaces of Learning in Neural Networks](https://huggingface.co/papers/2407.04797) (2024)\n* [An Empirical Analysis of Forgetting in Pre-trained Models with Incremental Low-Rank Updates](https://huggingface.co/papers/2405.18069) (2024)\n* [Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks](https://huggingface.co/papers/2405.15481) (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`"} |