AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes Colla-Q, a bit-allocation framework to maintain balanced performance across experts through an activation-entropy-based bit-width allocation algorithm that encourages each expert to operate collaboratively in the quantized model, thereby improving the overall MoE performance and reducing the dependen...
OverRep is proposed, an Overcomplete Reparameterization framework for structured LLM pruning that temporarily overparameterizes the recovery module during training to absorb complex knowledge distilled from the original model.
Ensuring effective transfer learning for vision-language models without compromising their generalization performance is crucial. However, many existing methods overlook data characteristics and simply reuse the training strategies adopted during pre-training. Specifically, they treat same-class samples as distinct ins...
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