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05/19/2023
LLM-Pruner: On the Structural Pruning of Large Language Models
Large language models (LLMs) have shown remarkable capabilities in langu...
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05/18/2023
Structural Pruning for Diffusion Models
Generative modeling has recently undergone remarkable advancements, prim...
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01/30/2023
DepGraph: Towards Any Structural Pruning
Structural pruning enables model acceleration by removing structurally-g...
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07/27/2022
Federated Selective Aggregation for Knowledge Amalgamation
In this paper, we explore a new knowledge-amalgamation problem, termed F...
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05/16/2022
Prompting to Distill: Boosting Data-Free Knowledge Distillation via Reinforced Prompt
Data-free knowledge distillation (DFKD) conducts knowledge distillation ...
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03/07/2022
Knowledge Amalgamation for Object Detection with Transformers
Knowledge amalgamation (KA) is a novel deep model reusing task aiming to...
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12/12/2021
Up to 100x Faster Data-free Knowledge Distillation
Data-free knowledge distillation (DFKD) has recently been attracting inc...
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10/27/2021
Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data
Knowledge distillation (KD) aims to craft a compact student model that i...
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05/18/2021
Contrastive Model Inversion for Data-Free Knowledge Distillation
Model inversion, whose goal is to recover training data from a pre-train...
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07/10/2020
Impression Space from Deep Template Network
It is an innate ability for humans to imagine something only according t...
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12/23/2019
Data-Free Adversarial Distillation
Knowledge Distillation (KD) has made remarkable progress in the last few...
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06/24/2019