Updated the Citation

CITATION.cff

@@ -1,8 +1,7 @@
-
 cff-version: 1.2.0
 title: >-
-  Software for Dataset-wide XAI: From Local Explanations to
-  Global Insights with Zennit, CoRelAy, and ViRelAy
+  Software for dataset-wide XAI: From local explanations to
+  global insights with Zennit, CoRelAy, and ViRelAy
 message: >-
   If you use this software, please cite it using the
   metadata from this file.
@@ -11,49 +10,76 @@ authors:
   - given-names: Christopher J.
     family-names: Anders
     orcid: 'https://orcid.org/0000-0003-3295-8486'
+    affiliation: RIKEN Center for Advanced Intelligence Project
   - given-names: David
     family-names: Neumann
     orcid: 'https://orcid.org/0000-0003-1907-8329'
+    affiliation: >-
+      Fraunhofer Institute for Telecommunications,
+      Heinrich-Hertz-Institut, HHI
   - given-names: Wojciech
     family-names: Samek
     orcid: 'https://orcid.org/0000-0002-6283-3265'
+    affiliation: >-
+      Fraunhofer Institute for Telecommunications,
+      Heinrich-Hertz-Institut, HHI
   - given-names: Klaus-Robert
     family-names: Müller
     orcid: 'https://orcid.org/0000-0002-3861-7685'
+    affiliation: Technische Universität Berlin
   - given-names: Sebastian
     family-names: Lapuschkin
     orcid: 'https://orcid.org/0000-0002-0762-7258'
+    affiliation: >-
+      Fraunhofer Institute for Telecommunications,
+      Heinrich-Hertz-Institut, HHI
 identifiers:
   - type: doi
-    value: 10.48550/arXiv.2106.13200
-    description: arXiv Preprint
+    value: 10.1371/journal.pone.0336683
+    description: DOI
   - type: url
-    value: 'https://arxiv.org/abs/2106.13200'
-    description: arXiv Preprint
-repository-code: 'https://github.com/virelay/corelay.git'
-url: 'https://corelay.readthedocs.io/en/latest/'
+    value: >-
+      https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0336683
+    description: PLOS One
+repository-code: 'https://github.com/virelay/virelay.git'
+url: 'https://virelay.readthedocs.io/en/latest/'
 abstract: >-
-  Deep Neural Networks (DNNs) are known to be strong
-  predictors, but their prediction strategies can rarely be
-  understood. With recent advances in Explainable Artificial
-  Intelligence (XAI), approaches are available to explore
-  the reasoning behind those complex models' predictions.
-  Among post-hoc attribution methods, Layer-wise Relevance
-  Propagation (LRP) shows high performance. For deeper
-  quantitative analysis, manual approaches exist, but
-  without the right tools they are unnecessarily labor
-  intensive. In this software paper, we introduce three
-  software packages targeted at scientists to explore model
-  reasoning using attribution approaches and beyond: (1)
-  Zennit - a highly customizable and intuitive attribution
-  framework implementing LRP and related approaches in
-  PyTorch, (2) CoRelAy - a framework to easily and quickly
-  construct quantitative analysis pipelines for dataset-wide
-  analyses of explanations, and (3) ViRelAy - a
-  web-application to interactively explore data,
-  attributions, and analysis results. With this, we provide
-  a standardized implementation solution for XAI, to
-  contribute towards more reproducibility in our field.
+  The predictive capabilities of Deep Neural Networks (DNNs)
+  are well-established, yet the underlying mechanisms
+  driving these predictions often remain opaque. The advent
+  of Explainable Artificial Intelligence (XAI) has
+  introduced novel methodologies to explore the reasoning
+  behind complex model predictions of complex models. Among
+  post-hoc attribution methods, Layer-wise Relevance
+  Propagation (LRP) has demonstrated notable adaptability
+  and performance for explaining individual predictions –
+  provided the method is used to its full potential. For
+  deeper dataset-wide and quantitative analyses, however,
+  the manual inspection of individual attribution maps
+  remains unnecessarily labor-intensive and time consuming.
+  While several approaches for dataset-wide XAI-analyses
+  have been proposed, unified and accessible implementations
+  of such tools are still lacking. Furthermore, there is a
+  notable absence of dedicated visualization and analysis
+  software to support stakeholders in interpreting both
+  local and global XAI results effectively. This gap
+  underscores the need for comprehensive software tools that
+  facilitate both granular and holistic understanding of
+  model behavior, as well as easing the adaptability of XAI
+  in applications and the sciences. To address these
+  challenges, we present three software packages designed to
+  facilitate the exploration of model reasoning using
+  attribution approaches and beyond: (1) Zennit – a highly
+  customizable and intuitive attribution framework
+  implementing LRP and related methods in PyTorch, (2)
+  CoRelAy – a framework to easily and quickly construct
+  quantitative analysis pipelines for dataset-wide analyses
+  of explanations, and (3) ViRelAy – an interactive
+  web-application for exploring data, attributions, and
+  analysis results. By providing a standardized
+  implementation for XAI, we aim to promote reproducibility
+  in our field and empower scientists and practitioners to
+  uncover the intricacies of complex model behavior.
 keywords:
   - Explainable Artificial Intelligence
   - XAI
@@ -64,4 +90,9 @@ keywords:
   - Zennit
   - CoRelAy
   - ViRelAy
-license: GPL-3.0-or-later AND LGPL-3.0-or-later
+license:
+  - GPL-3.0-or-later
+  - LGPL-3.0-or-later
+commit: 8c9b9286ab4bf8ec59eafdceda6bb009c72e4b76
+version: 1.0.0
+date-released: '2025-08-06'

README.md

@@ -29,16 +29,19 @@ For more information about CoRelAy, getting started guides, in-depth tutorials,
 If you find CoRelAy useful for your research, why not cite our related [paper](https://arxiv.org/abs/2106.13200):
 
 ```bibtex
-@article{anders2021software,
-  author  = {Anders, Christopher J. and
+@article{bibliography:software-for-dataset-wide-xai,
+  author  = {Anders, {Christopher J.} and
              Neumann, David and
              Samek, Wojciech and
-             Müller, Klaus-Robert and
+             Müller, {Klaus-Robert} and
              Lapuschkin, Sebastian},
-  title   = {Software for Dataset-wide XAI: From Local Explanations to Global Insights with {Zennit}, {CoRelAy}, and {ViRelAy}},
-  year    = {2021},
-  volume  = {abs/2106.13200},
-  journal = {CoRR}
+  title   = {Software for {dataset-wide} {XAI}: From local explanations to global insights with Zennit, {CoRelAy}, and {ViRelAy}},
+  year    = {2026},
+  month   = jan,
+  journal = {{PLOS} One},
+  volume  = {21},
+  number  = {1},
+  pages   = {1--38}
 }
 ```
 

src/corelay/processor/distance.py

@@ -56,12 +56,10 @@ class SciPyPDist(Distance):
     * "pnorm"
     * "jaccard", "jacc", "ja", "j"
     * "jensenshannon", "js"
-    * "kulczynski1"
     * "mahalanobis", "mahal", "mah"
     * "rogerstanimoto"
     * "russellrao"
     * "seuclidean", "se", "s"
-    * "sokalmichener"
     * "sokalsneath"
     * "sqeuclidean", "sqe", "sqeuclid"
     * "yule"
@@ -124,7 +122,6 @@ def function(self, data: typing.Any) -> typing.Any:
             'j',
             'jensenshannon',
             'js',
-            'kulczynski1',
             'mahalanobis',
             'mahal',
             'mah',
@@ -133,7 +130,6 @@ def function(self, data: typing.Any) -> typing.Any:
             'seuclidean',
             'se',
             's',
-            'sokalmichener',
             'sokalsneath',
             'sqeuclidean',
             'sqe',

tests/linters/cspell/.cspell.json

@@ -148,6 +148,7 @@
         "ifmat",
         "imgmath",
         "incollection",
+        "Institut",
         "intersphinx",
         "issn",
         "issuetitle",
@@ -191,6 +192,7 @@
         "pdist",
         "pearsonr",
         "Pickler",
+        "PLOS",
         "Plugboards",
         "pnorm",
         "posargs",
@@ -203,6 +205,7 @@
         "rcfile",
         "reftypes",
         "regionref",
+        "RIKEN",
         "rodolphebarbanneau",
         "rogerstanimoto",
         "russellrao",
@@ -224,6 +227,7 @@
         "SSIM",
         "synset",
         "tamasfe",
+        "Technische",
         "testpaths",
         "texlive",
         "toarray",
@@ -234,6 +238,7 @@
         "ufunc",
         "Ulrike",
         "umap",
+        "Universität",
         "urldate",
         "varnames",
         "vimrc",