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CTUAvastLab · Jun 6, 2024 · b402491 · b402491
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diff --git a/README.md b/README.md
@@ -38,29 +38,48 @@ Julia v1.9 or later is required.
 
 ## Citation
 
-For citing, please use the following entry for the [original paper](https://jmlr.org/papers/v23/21-0174.html):
-```
-@article{Mandlik2021,
-  author  = {Šimon Mandlík and Matěj Račinský and Viliam Lisý and Tomáš Pevný},
-  title   = {JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data},
-  journal = {Journal of Machine Learning Research},
-  year    = {2022},
-  volume  = {23},
-  number  = {298},
-  pages   = {1--5},
-  url     = {http://jmlr.org/papers/v23/21-0174.html}
-}
-```
-
-and the following for this implementation (fill in the used `version`):
-```
-@software{Mill,
-  author = {Tomas Pevny and Simon Mandlik},
-  title = {Mill.jl framework: a flexible library for (hierarchical) multi-instance learning},
-  url = {https://github.com/CTUAvastLab/Mill.jl},
-  version = {...},
-}
-```
+Kindly cite our work with the following entries if you find it interesting, please:
+
+* [*JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data*](https://jmlr.org/papers/v23/21-0174.html)
+
+  ```
+  @article{Mandlik2021,
+    author  = {Šimon Mandlík and Matěj Račinský and Viliam Lisý and Tomáš Pevný},
+    title   = {JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data},
+    journal = {Journal of Machine Learning Research},
+    year    = {2022},
+    volume  = {23},
+    number  = {298},
+    pages   = {1--5},
+    url     = {http://jmlr.org/papers/v23/21-0174.html}
+  }
+  ```
+
+* [*Malicious Internet Entity Detection Using Local Graph Inference*](https://ieeexplore.ieee.org/document/10418120) (practical `Mill.jl` application)
+
+  ```
+  @article{Mandlik2024,
+    author  ={Mandlík, Šimon and Pevný, Tomáš and Šmídl, Václav and Bajer, Lukáš},
+    journal ={IEEE Transactions on Information Forensics and Security},
+    title   ={Malicious Internet Entity Detection Using Local Graph Inference},
+    year    ={2024},
+    volume  ={19},
+    number  ={},
+    pages   ={3554-3566},
+    doi     ={10.1109/TIFS.2024.3360867}
+  }
+  ```
+
+* this implementation (fill in the used `version`):
+
+  ```
+  @software{Mill,
+    author = {Tomas Pevny and Simon Mandlik},
+    title = {Mill.jl framework: a flexible library for (hierarchical) multi-instance learning},
+    url = {https://github.com/CTUAvastLab/Mill.jl},
+    version = {...},
+  }
+  ```
 
 ## Contribution guidelines
 

diff --git a/docs/src/citation.md b/docs/src/citation.md
@@ -1,25 +1,44 @@
 # Citation
 
-For citing, please use the following entry for the [original paper](https://jmlr.org/papers/v23/21-0174.html):
-```
-@article{Mandlik2021,
-  author  = {Šimon Mandlík and Matěj Račinský and Viliam Lisý and Tomáš Pevný},
-  title   = {JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data},
-  journal = {Journal of Machine Learning Research},
-  year    = {2022},
-  volume  = {23},
-  number  = {298},
-  pages   = {1--5},
-  url     = {http://jmlr.org/papers/v23/21-0174.html}
-}
-```
+Kindly cite our work with the following entries if you find it interesting, please:
 
-and the following for the implementation (fill in the used `version`):
-```
-@software{mill2018,
-  author = {Tomas Pevny and Simon Mandlik},
-  title = {Mill.jl framework: a flexible library for (hierarchical) multi-instance learning},
-  url = {https://github.com/CTUAvastLab/Mill.jl},
-  version = {...},
-}
-```
+* [*JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data*](https://jmlr.org/papers/v23/21-0174.html)
+
+  ```
+  @article{Mandlik2021,
+    author  = {Šimon Mandlík and Matěj Račinský and Viliam Lisý and Tomáš Pevný},
+    title   = {JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data},
+    journal = {Journal of Machine Learning Research},
+    year    = {2022},
+    volume  = {23},
+    number  = {298},
+    pages   = {1--5},
+    url     = {http://jmlr.org/papers/v23/21-0174.html}
+  }
+  ```
+
+* [*Malicious Internet Entity Detection Using Local Graph Inference*](https://ieeexplore.ieee.org/document/10418120) (practical `Mill.jl` application)
+
+  ```
+  @article{Mandlik2024,
+    author  ={Mandlík, Šimon and Pevný, Tomáš and Šmídl, Václav and Bajer, Lukáš},
+    journal ={IEEE Transactions on Information Forensics and Security},
+    title   ={Malicious Internet Entity Detection Using Local Graph Inference},
+    year    ={2024},
+    volume  ={19},
+    number  ={},
+    pages   ={3554-3566},
+    doi     ={10.1109/TIFS.2024.3360867}
+  }
+  ```
+
+* this implementation (fill in the used `version`):
+
+  ```
+  @software{Mill,
+    author = {Tomas Pevny and Simon Mandlik},
+    title = {Mill.jl framework: a flexible library for (hierarchical) multi-instance learning},
+    url = {https://github.com/CTUAvastLab/Mill.jl},
+    version = {...},
+  }
+  ```