Update references to include JMLR on the main website

CITATION.cff

@@ -0,0 +1,38 @@
+cff-version: 1.2.0
+message: "If you use this software, please cite it as below."
+title: "AutoML Benchmark"
+version: 2.1.7
+license: "MIT"
+url: "https://github.com/openml/automlbenchmark"
+preferred-citation:
+  type: article
+  authors:
+  - family-names: "Gijsbers"
+    given-names: "Pieter"
+    orcid: "https://orcid.org/0000-0001-7346-8075"
+  - family-names: "de Paula Bueno"
+    given-names: "Marcos"
+  - family-names: "Coors"
+    given-names: "Stefan"
+    orcid: "https://orcid.org/0000-0001-7346-8075"
+  - family-names: "LeDell"
+    given-names: "Erin"
+  - family-names: "Poirier"
+    given-names: "Sébastien"
+  - family-names: "Thomas"
+    given-names: "Janek"
+    orcid: "https://orcid.org/0000-0003-4511-6245"
+  - family-names: "Bischl"
+    given-names: "Bernd"
+    orcid: "https://orcid.org/0000-0001-6002-6980"
+  - family-names: "Vanschoren"
+    given-names: "Joaquin"
+    orcid: "https://orcid.org/0000-0001-7044-9805"
+  journal: "Journal of Machine Learning Research"
+  start: 1 # First page number
+  end: 65 # Last page number
+  title: "AMLB: an AutoML Benchmark"
+  issue: 101
+  volume: 25
+  year: 2024
+  url: http://jmlr.org/papers/v25/22-0493.html

docs/website/contributing.html

@@ -206,20 +206,15 @@ <h3 id="cite">Citing AMLB</h3>
             When referring to the benchmark please cite
         </p>
         <div class="bibtex">
-            @misc{https://doi.org/10.48550/arxiv.2207.12560, <br />
-            &emsp; doi = {10.48550/ARXIV.2207.12560}, <br />
-            &emsp; url = {https://arxiv.org/abs/2207.12560}, <br />
-            &emsp; author = {Gijsbers, Pieter and Bueno, Marcos L. P. and Coors,
-            Stefan and LeDell, Erin and Poirier, S\'{e}bastien and Thomas, Janek
-            and Bischl, Bernd and Vanschoren, Joaquin}, <br />
-            &emsp; keywords = {Machine Learning (cs.LG), Machine Learning
-            (stat.ML), FOS: Computer and information sciences, FOS: Computer and
-            information sciences}, <br />
-            &emsp; title = {AMLB: an AutoML Benchmark}, <br />
-            &emsp; publisher = {arXiv}, <br />
-            &emsp; year = {2022}, <br />
-            &emsp; copyright = {Creative Commons Attribution 4.0 International}
-            <br />
+            @article{JMLR:v25:22-0493,<br />
+              author  = {Pieter Gijsbers and Marcos L. P. Bueno and Stefan Coors and Erin LeDell and S{{\'e}}bastien Poirier and Janek Thomas and Bernd Bischl and Joaquin Vanschoren},<br />
+              title   = {AMLB: an AutoML Benchmark},<br />
+              journal = {Journal of Machine Learning Research},<br />
+              year    = {2024},<br />
+              volume  = {25},<br />
+              number  = {101},<br />
+              pages   = {1--65},<br />
+              url     = {http://jmlr.org/papers/v25/22-0493.html}<br />
             }
           </div>
     </section>

docs/website/index.html

@@ -320,14 +320,13 @@ <h3>Easy to Extend</h3>
           <div class="flat-card">
             <h3>📄 Paper</h3>
             <div>
-              A preprint of our most recent paper is available on
-              <a href="https://arxiv.org/abs/2207.12560" target="_blank"
-                >ArXiv</a
-              >. It includes an in-depth discussion of the different design
-              decisions and its limiations, as well as a multi-faceted analysis
+              Our
+              <a href="https://jmlr.org/papers/v25/22-0493.html" target="_blank"
+                >JMLR</a
+              > paper introduces the benchmark. It includes an in-depth discussion of the different design
+              decisions and its limitations, as well as a multi-faceted analysis
               of results from large scale comparison across 9 frameworks on more
-              than 100 tasks.
-              <!-- https://arxiv.org/abs/1907.00909 -->
+              than 100 tasks conducted in 2023.
             </div>
           </div>
           <div class="flat-card">

docs/website/papers.html

@@ -165,11 +165,6 @@ <h2 class="paper-title">AMLB: an AutoML Benchmark</h2>
           Pieter Gijsbers, Marcos L. P. Bueno, Stefan Coors, Erin LeDell,
           Sébastien Poirier, Janek Thomas, Bernd Bischl and Joaquin Vanschoren
         </div>
-
-        <!-- <div class="paper-year">2019</div>
-      <div class="paper-venue">ICML 2019 AutoML Workshop</div>
-      <div class="paper-venue">cite</div> -->
-
         <div class="paper-abstract">
           Comparing different AutoML frameworks is notoriously challenging and
           often done incorrectly. We introduce an open and extensible benchmark
@@ -187,16 +182,64 @@ <h2 class="paper-title">AMLB: an AutoML Benchmark</h2>
           data sets, can be easily extended with other AutoML frameworks and
           tasks, and has a website with up-to-date results.
         </div>
+        <div class="paper-links">
+          <div class="hover-expand">
+            <strong>2024</strong>
+            <div>Journal of Machine Learning Research</div>
+          </div>
+          <a class="flat-button">
+            <label for="cite-2024">CITE</label>
+          </a>
+          <a href="https://jmlr.org/papers/volume25/22-0493/22-0493.pdf" target="_blank">PDF</a>
+          <a href="https://jmlr.org/papers/v25/22-0493.html" target="_blank">JMLR</a>
+        </div>
+        <div>
+          <input
+                  type="checkbox"
+                  id="cite-2024"
+                  class="hidden-content-checkbox"
+          />
+          <div class="hidden-content bibtex">
+            @article{JMLR:v25:22-0493,<br />
+            author  = {Pieter Gijsbers and Marcos L. P. Bueno and Stefan Coors and Erin LeDell and S{{\'e}}bastien Poirier and Janek Thomas and Bernd Bischl and Joaquin Vanschoren},<br />
+            title   = {AMLB: an AutoML Benchmark},<br />
+            journal = {Journal of Machine Learning Research},<br />
+            year    = {2024},<br />
+            volume  = {25},<br />
+            number  = {101},<br />
+            pages   = {1--65},<br />
+            url     = {http://jmlr.org/papers/v25/22-0493.html}<br />
+            }
+          </div>
+        </div>
+      </div>
+      <div class="paper">
+        <h2 class="paper-title">[preprint, '22] AMLB: an AutoML Benchmark</h2>
+        <div class="paper-authors">
+          Pieter Gijsbers, Marcos L. P. Bueno, Stefan Coors, Erin LeDell,
+          Sébastien Poirier, Janek Thomas, Bernd Bischl and Joaquin Vanschoren
+        </div>
+
+        <!-- <div class="paper-year">2019</div>
+      <div class="paper-venue">ICML 2019 AutoML Workshop</div>
+      <div class="paper-venue">cite</div> -->
+
+        <div class="paper-abstract">
+          This is the preprint of the 2024 JMLR paper, the first submission before a revision.
+          This version which reports on the experimental results obtained in 2021.
+          Please only cite this paper if you specifically refer to results reported herein,
+          and cannot use the JMLR paper for that purpose.
+        </div>
         <div class="paper-links">
           <div class="hover-expand">
             <strong>2022</strong>
-            <div>Under Review</div>
+            <div>preprint</div>
           </div>
           <a class="flat-button">
             <label for="cite-2022">CITE</label>
           </a>
-          <a href="https://arxiv.org/pdf/2207.12560.pdf" target="_blank">PDF</a>
-          <a href="https://arxiv.org/abs/2207.12560" target="_blank">ArXiv</a>
+          <a href="https://arxiv.org/pdf/2207.12560v1.pdf" target="_blank">PDF</a>
+          <a href="https://arxiv.org/abs/2207.12560v1" target="_blank">ArXiv</a>
         </div>
         <div>
           <input