MLWQ: Efficient Small Language Model Deployment via Multi-Level Weight Quantization (2025.emnlp-main)
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| Challenge: | Existing methods for efficient deployment of small language models face inefficient bit-width allocation and insufficient fine-grained quantization adjustments. |
| Approach: | They propose a weight quantization technique that facilitates efficient deployment of SLMs . they propose to combine inter-layer loss and intra-layer salience to achieve better allocation . |
| Outcome: | Experimental results show that multi-level weight quantization achieves competitive performance compared to state-of-the-art methods. |
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