Results 21 to 30 of about 219,795 (335)
Making Monolingual Sentence Embeddings Multilingual Using Knowledge Distillation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2020 We present an easy and efficient method to extend existing sentence embedding models to new languages. This allows to create multilingual versions from previously monolingual models.
Nils Reimers, Iryna Gurevych
semanticscholar +1 more source
The Advances in the Special Microwave Effects of the Heterogeneous Catalytic Reactions
Frontiers in Chemistry, 2020 In the present, microwave field has been widely used in chemical processes as an important means of intensification. The heterogeneous catalysts coupling with microwave has been shown to have many advantages, such as high catalytic performance and ...
Hong Li +5 more
doaj +1 more source
Relational Knowledge Distillation [PDF]
Computer Vision and Pattern Recognition, 2019 Knowledge distillation aims at transferring knowledge acquired in one model (a teacher) to another model (a student) that is typically smaller. Previous approaches can be expressed as a form of training the student to mimic output activations of ...
Wonpyo Park +3 more
semanticscholar +1 more source
Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning [PDF]
Computer Vision and Pattern Recognition, 2022 Federated Learning (FL) is an emerging distributed learning paradigm under privacy constraint. Data heterogeneity is one of the main challenges in FL, which results in slow convergence and degraded performance.
Lin Zhang +4 more
semanticscholar +1 more source
Physical Review Letters, 2009 Revised abstract, introduction and conclusion.
Manuel Forster +2 more
openaire +3 more sources
TinyViT: Fast Pretraining Distillation for Small Vision Transformers [PDF]
European Conference on Computer Vision, 2022 Vision transformer (ViT) recently has drawn great attention in computer vision due to its remarkable model capability. However, most prevailing ViT models suffer from huge number of parameters, restricting their applicability on devices with limited ...
Kan Wu +6 more
semanticscholar +1 more source
Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-Step [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 Chain-of-thought prompting (e.g., “Let’s think step-by-ste”) primes large language models to verbalize rationalization for their predictions. While chain-of-thought can lead to dramatic performance gains, benefits appear to emerge only for sufficiently ...
Liunian Harold Li +5 more
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Focal and Global Knowledge Distillation for Detectors [PDF]
Computer Vision and Pattern Recognition, 2021 Knowledge distillation has been applied to image classification successfully. However, object detection is much more sophisticated and most knowledge distillation methods have failed on it.
Zhendong Yang +6 more
semanticscholar +1 more source
Warta LPM, 2023 The problems the Smoke-liquid Craftsman Group often faces are production capacity, product quality, and low selling prices. Low production capacity due to the limited ability distillation machine.
Sukamta Sukamta +4 more
doaj +1 more source
On Distillation of Guided Diffusion Models [PDF]
Computer Vision and Pattern Recognition, 2022 Classifier-free guided diffusion models have recently been shown to be highly effective at high-resolution image generation, and they have been widely used in large-scale diffusion frameworks including DALL.E 2, Stable Diffusion and Imagen.
Chenlin Meng +5 more
semanticscholar +1 more source