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data/2408.07089.json

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+{"paper_url": "https://huggingface.co/papers/2408.07089", "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* [DotaMath: Decomposition of Thought with Code Assistance and Self-correction for Mathematical Reasoning](https://huggingface.co/papers/2407.04078) (2024)\n* [Key-Point-Driven Mathematical Reasoning Distillation of Large Language Model](https://huggingface.co/papers/2407.10167) (2024)\n* [Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models](https://huggingface.co/papers/2406.17294) (2024)\n* [UniCoder: Scaling Code Large Language Model via Universal Code](https://huggingface.co/papers/2406.16441) (2024)\n* [InverseCoder: Unleashing the Power of Instruction-Tuned Code LLMs with Inverse-Instruct](https://huggingface.co/papers/2407.05700) (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`"}

data/2408.07410.json

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+{"paper_url": "https://huggingface.co/papers/2408.07410", "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* [AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out Strategies](https://huggingface.co/papers/2408.06567) (2024)\n* [Exploring Advanced Large Language Models with LLMsuite](https://huggingface.co/papers/2407.12036) (2024)\n* [Open Artificial Knowledge](https://huggingface.co/papers/2407.14371) (2024)\n* [DataComp-LM: In search of the next generation of training sets for language models](https://huggingface.co/papers/2406.11794) (2024)\n* [Qwen2 Technical Report](https://huggingface.co/papers/2407.10671) (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`"}

data/2408.07547.json

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+{"paper_url": "https://huggingface.co/papers/2408.07547", "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* [VNet: A GAN-based Multi-Tier Discriminator Network for Speech Synthesis Vocoders](https://huggingface.co/papers/2408.06906) (2024)\n* [FA-GAN: Artifacts-free and Phase-aware High-fidelity GAN-based Vocoder](https://huggingface.co/papers/2407.04575) (2024)\n* [FLY-TTS: Fast, Lightweight and High-Quality End-to-End Text-to-Speech Synthesis](https://huggingface.co/papers/2407.00753) (2024)\n* [Autoregressive Speech Synthesis without Vector Quantization](https://huggingface.co/papers/2407.08551) (2024)\n* [Speech Bandwidth Expansion Via High Fidelity Generative Adversarial Networks](https://huggingface.co/papers/2407.18571) (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`"}