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{"paper_url": "https://huggingface.co/papers/2504.07964", "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* [R2-T2: Re-Routing in Test-Time for Multimodal Mixture-of-Experts](https://huggingface.co/papers/2502.20395) (2025)\n* [Every Expert Matters: Towards Effective Knowledge Distillation for Mixture-of-Experts Language Models](https://huggingface.co/papers/2502.12947) (2025)\n* [Evaluating Expert Contributions in a MoE LLM for Quiz-Based Tasks](https://huggingface.co/papers/2502.17187) (2025)\n* [Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language Models](https://huggingface.co/papers/2504.07807) (2025)\n* [Convergence Rates for Softmax Gating Mixture of Experts](https://huggingface.co/papers/2503.03213) (2025)\n* [From Dense to Dynamic: Token-Difficulty Driven MoEfication of Pre-Trained LLMs](https://huggingface.co/papers/2502.12325) (2025)\n* [Efficiently Editing Mixture-of-Experts Models with Compressed Experts](https://huggingface.co/papers/2503.00634) (2025)\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`"}
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