diff --git a/joss/paper.bib b/joss/paper.bib
index 3c4fe825..6e40e9e7 100644
--- a/joss/paper.bib
+++ b/joss/paper.bib
@@ -166,4 +166,60 @@ @inproceedings{turing
   year      = {2018},
   url       = {http://proceedings.mlr.press/v84/ge18b.html},
   biburl    = {https://dblp.org/rec/bib/conf/aistats/GeXG18},
+}
+
+@software{DatagenCopulaBased_1,
+  author       = {Krzysztof Domino and
+                  Adam and
+                  Oskar Laverny and
+                  Julia TagBot},
+  title        = {iitis/DatagenCopulaBased.jl: v1.4.2},
+  month        = may,
+  year         = 2023,
+  publisher    = {Zenodo},
+  version      = {v1.4.2},
+  doi          = {10.5281/zenodo.7944064},
+  url          = {https://doi.org/10.5281/zenodo.7944064}
+}
+
+@misc{DatagenCopulaBased_2,
+      title={Introducing higher order correlations to marginals' subset of multivariate data by means of Archimedean copulas}, 
+      author={Krzysztof Domino and Adam Glos},
+      year={2018},
+      eprint={1803.07813},
+      archivePrefix={arXiv},
+      primaryClass={cs.DS}
+}
+
+@misc{DatagenCopulaBased_3,
+      title={Selected Methods for non-Gaussian Data Analysis}, 
+      author={Krzysztof Domino},
+      year={2019},
+      eprint={1811.10486},
+      archivePrefix={arXiv},
+      primaryClass={stat.ME}
+}
+
+@article{DatagenCopulaBased_4,
+  title={Multivariate cumulants in outlier detection for financial data analysis},
+  author={Domino, Krzysztof},
+  journal={Physica A: Statistical Mechanics and its Applications},
+  volume={558},
+  pages={124995},
+  year={2020},
+  publisher={Elsevier}
+}
+
+@software{BivariateCopulas,
+  author       = {Ander Gray and
+                  Jasper Behrensdorf and
+                  amrods and
+                  Christian Schilling},
+  title        = {AnderGray/BivariateCopulas.jl: 0.1.5},
+  month        = dec,
+  year         = 2023,
+  publisher    = {Zenodo},
+  version      = {v0.1.5},
+  doi          = {10.5281/zenodo.10412898},
+  url          = {https://doi.org/10.5281/zenodo.10412898}
 }
\ No newline at end of file
diff --git a/joss/paper.md b/joss/paper.md
index f2dbba5d..7302b1cf 100644
--- a/joss/paper.md
+++ b/joss/paper.md
@@ -35,7 +35,7 @@ The Julia package `Copulas.jl` brings most standard copula-related features into
 
 The R package `copula` [@r_copula_citation1; @r_copula_citation2; @r_copula_citation3; @r_copula_citation4] is the gold standard when it comes to sampling, estimating, or simply working around dependence structures. However, in other languages, the available tools are not as developped and/or not as recognised. We bridge the gap in the Julian ecosystem with this Julia-native implementation. Due to the very flexible type system in Julia, our code expressiveness and tidyness will increase its usability and maintenability in the long-run. Type-stability allows sampling in arbitrary precision without requiering more code, and Julia's multiple dispatch yields most of the below-described applications.
 
-There are competing packages in Julia, such as [`BivariateCopulas.jl`](https://github.com/AnderGray/BivariateCopulas.jl) which only deals with a few models in bivariate settings but has very nice graphs, or [`DatagenCopulaBased.jl`](https://github.com/iitis/DatagenCopulaBased.jl), which only provides sampling and does not have exactly the same models as `Copulas.jl`. While not fully covering out both of these package's functionality (mostly because the three projects chose different copulas to implement), `Copulas.jl` is clearly the must fully featured, and brings, as a key feature, the complience with the broader ecosystem.
+There are competing packages in Julia, such as [`BivariateCopulas.jl`](https://github.com/AnderGray/BivariateCopulas.jl) [@BivariateCopulas] which only deals with a few models in bivariate settings but has very nice graphs, or [`DatagenCopulaBased.jl`](https://github.com/iitis/DatagenCopulaBased.jl) [@DatagenCopulaBased_1; @DatagenCopulaBased_2; @DatagenCopulaBased_3; @DatagenCopulaBased_4], which only provides sampling and does not have exactly the same models as `Copulas.jl`. While not fully covering out both of these package's functionality (mostly because the three projects chose different copulas to implement), `Copulas.jl` is clearly the must fully featured, and brings, as a key feature, the complience with the broader ecosystem.
 
 # Examples