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@CASE-Lab-UMD

CASE Lab@UMD

CASE (Collaborative, Automated, Scalable, and Efficient Intelligence) Lab is an active research group at University of Maryland College Park.

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  1. LLM-Drop LLM-Drop Public

    The official implementation of the paper "What Matters in Transformers? Not All Attention is Needed".

    Python 185 22

  2. Unified-MoE-Compression Unified-MoE-Compression Public

    The official implementation of the paper "Towards Efficient Mixture of Experts: A Holistic Study of Compression Techniques (TMLR)".

    Python 87 6

  3. Router-Tuning-Mixture-of-Depths Router-Tuning-Mixture-of-Depths Public

    The open-source Mixture of Depths code and the official implementation of the paper "Router-Tuning: A Simple and Effective Approach for Enabling Dynamic Depth in Transformers. (EMNLP 2025)"

    Python 26 3

  4. Capacity-Aware-MoE Capacity-Aware-MoE Public

    The official implementation of the paper "Capacity-Aware Inference: Mitigating the Straggler Effect in Mixture of Experts".

    Python 11

  5. FLoRA FLoRA Public

    Python 7 1

  6. counterfactual_fairness_2025 counterfactual_fairness_2025 Public

    Python 7

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