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 | **License** | **Documentation** | **Build Status** | **Coverage** | **Citation** |
 |:-----------------:|:----------------:|:----------------:|:----------------:|:----------------:|
-| [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) | [![doc](https://img.shields.io/badge/docs-dev-blue.svg)](https://github.com/sshin23/SIMDiff.jl/dev)  | [![build](https://github.com/sshin23/SIMDiff.jl/actions/workflows/test.yml/badge.svg)](https://github.com/sshin23/SIMDiff.jl/actions/workflows/test.yml) | [![codecov](https://codecov.io/gh/sshin23/SIMDiff.jl/branch/main/graph/badge.svg?token=8ViJWBWnZt)](https://codecov.io/gh/sshin23/SIMDiff.jl) |
+| [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) | [![doc](https://img.shields.io/badge/docs-dev-blue.svg)](https://sshin23.github.io/SIMDiff.jl/)  | [![build](https://github.com/sshin23/SIMDiff.jl/actions/workflows/test.yml/badge.svg)](https://github.com/sshin23/SIMDiff.jl/actions/workflows/test.yml) | [![codecov](https://codecov.io/gh/sshin23/SIMDiff.jl/branch/main/graph/badge.svg?token=8ViJWBWnZt)](https://codecov.io/gh/sshin23/SIMDiff.jl) |
 
 ## Introduction
 SIMDiff.jl employs what we call **SIMD abstraction for nonlinear programs** (NLPs), which allows for the **preservation of the parallelizable structure** within the model equations, facilitating **efficient, parallel derivative evaluations** on the **GPU**.