diff --git a/Project.toml b/Project.toml
index 331ef6cd..54f7baab 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "PSIS"
 uuid = "ce719bf2-d5d0-4fb9-925d-10a81b42ad04"
 authors = ["Seth Axen <seth.axen@gmail.com> and contributors"]
-version = "0.7.0"
+version = "0.7.1"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
diff --git a/README.md b/README.md
index daebe605..0e7a5794 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,6 @@
 # PSIS
 
-[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://psis.julia.arviz.org/stable)
-[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://psis.julia.arviz.org/dev)
+[![Docs](https://img.shields.io/badge/docs-ArviZ-blue.svg)](https://julia.arviz.org/PSIS)
 [![Build Status](https://github.com/arviz-devs/PSIS.jl/workflows/CI/badge.svg)](https://github.com/arviz-devs/PSIS.jl/actions)
 [![Coverage](https://codecov.io/gh/arviz-devs/PSIS.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/arviz-devs/PSIS.jl)
 [![Code Style: Blue](https://img.shields.io/badge/code%20style-blue-4495d1.svg)](https://github.com/invenia/BlueStyle)
diff --git a/docs/src/index.md b/docs/src/index.md
index 98335fd0..ac7db4da 100644
--- a/docs/src/index.md
+++ b/docs/src/index.md
@@ -4,11 +4,6 @@ CurrentModule = PSIS
 
 # PSIS
 
-[![Build Status](https://github.com/arviz-devs/PSIS.jl/workflows/CI/badge.svg)](https://github.com/arviz-devs/PSIS.jl/actions)
-[![Coverage](https://codecov.io/gh/arviz-devs/PSIS.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/arviz-devs/PSIS.jl)
-[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
-[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)
-
 PSIS.jl implements the Pareto smoothed importance sampling (PSIS) algorithm from [^VehtariSimpson2021].
 
 Given a set of importance weights used in some estimator, PSIS both improves the reliability of the estimates by smoothing the importance weights and acts as a diagnostic of the reliability of the estimates.