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Add SDMPrune paper (#153)

* add SDMPrune paper* add SDMPrune paper---------Co-authored-by: ChengchaoShen <scc@csu.com>

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`@@ -463,6 +463,7 @@ python3 download_pdfs.py # The code is generated by Doubao AI`
`463`	`463`	`\|2024.01\|[Admm Pruning] Fast and Optimal Weight Update for Pruned Large Language Models(@fmph.uniba.sk)\|[[pdf]](https://arxiv.org/pdf/2401.02938.pdf)\|[[admm-pruning]](https://github.com/fmfi-compbio/admm-pruning)![](https://img.shields.io/github/stars/fmfi-compbio/admm-pruning.svg?style=social)\|⭐️\|`
`464`	`464`	`\|2024.01\|[FFSplit] FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference(@1Rice University etc)\|[[pdf]](https://arxiv.org/pdf/2401.04044.pdf)\| ⚠️\|⭐️\|`
`465`	`465`	`\|2025.03\|🔥[Simba] Sparsified State-Space Models are Efficient Highway Networks(@KAIST)\|[[pdf]](https://arxiv.org/abs/2505.20698)\|[[Simba]](https://github.com/woominsong/Simba)![](https://img.shields.io/github/stars/woominsong/Simba.svg?style=social)\|⭐️\|`
	`466`	`+\|2025.06\|[SDMPrune] SDMPrune: Self-Distillation MLP Pruning for Efficient Large Language Models (@CSU)\|[[pdf]](https://arxiv.org/abs/2506.11120)\|[[SDMPrune]](https://github.com/visresearch/SDMPrune)![](https://img.shields.io/github/stars/visresearch/SDMPrune.svg?style=social&label=Star)\|⭐️⭐️\|`
`466`	`467`
`467`	`468`	`###📖Mixture-of-Experts(MoE) LLM Inference ([©️back👆🏻](#paperlist))`
`468`	`469`	`<divid="Mixture_of_Experts_LLM_Inference"></div>`

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