NT-Xent
Normalized Temperature-scaled Cross Entropy Loss
**NT-Xent**, or **Normalized Temperature-scaled Cross Entropy Loss**, is a loss function. Let $\text{sim}\left(\mathbf{u}, \mathbf{v}\right) = \mathbf{u}^{T}\mathbf{v}/||\mathbf{u}|| ||\mathbf{v}||$ denote the cosine similarity between two vectors $\mathbf{u}$ and $\mathbf{v}$. Then the loss function for a positive pair of examples $\left(i, j\right)$ is :

$$ \mathbb{l}\_{i,j} = -\log\frac{\exp\left(\text{sim}\left(\mathbf{z}\_{i}, \mathbf{z}\_{j}\right)/\tau\right)}{\sum^{2N}\_{k=1}\mathcal{1}\_{[k\neq{i}]}\exp\left(\text{sim}\left(\mathbf{z}\_{i}, \mathbf{z}\_{k}\right)/\tau\right)}$$

where $\mathcal{1}\_{[k\neq{i}]} \in ${$0, 1$} is an indicator function evaluating to $1$ iff $k\neq{i}$ and $\tau$ denotes a temperature parameter. The final loss is computed across all positive pairs, both $\left(i, j\right)$ and $\left(j, i\right)$, in a mini-batch.

Source: [SimCLR](https://paperswithcode.com/method/simclr)
Improved Deep Metric Learning with Multi-class N-pair Loss Objective
https://paperswithcode.com/paper/improved-deep-metric-learning-with-multi
Improved Deep Metric Learning with Multi-class N-pair Loss Objective