Mar 29, 2023 · In contrast to common closed-form similarity measures, ContraSim learns a parameterized measure by using both similar and dissimilar examples.
Jun 16, 2024 · Motivated by this, we introduce ContraSim, a new similarity measure for interpreting NNs, based on contrastive learning (CL) (Chen et al., 2020; ...
May 24, 2023 · In contrast to common closed-form similarity measures, ContraSim learns a parameterized measure by using both similar and dissimilar examples.
In this work, we develop a new similarity measure, dubbed ContraSim, based on contrastive learning. In contrast to common closed-form similarity measures, ...
Sep 20, 2024 · Motivated by this, we introduce ContraSim, a new similarity measure for interpreting NNs, based on contrastive learning (CL) (Chen et al., 2020; ...
Sep 22, 2024 · ContraSim learns a parameterized similarity measure using both similar and dissimilar examples, in contrast to common closed-form similarity ...
Comparing different models allows one to analyze how different aspects like network architecture, training set, and model size affect the model's learned ...
Analyzing Neural Representations Based on Contrastive Learning ...
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ContraSim – Analyzing Neural Representations Based on Contrastive Learning. Adir Rahamim, Yonatan Belinkov · Computer Science. Research output: Chapter in Book ...
ContraSim – Analyzing Neural Representations Based on Contrastive Learning ... In this work, we develop a new similarity measure, dubbed ContraSim, based on ...
In contrast to common closed-form similarity measures, ContraSim learns a parameterized measure by using both similar and dissimilar examples. Contrastive ...