Refresh ER schema diagrams (1-12 of 12)

tgbl-coin/README.md

@@ -19,3 +19,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/tgbl-coin")
 task = relbench.load_task("relbench/tgb/tgbl-coin", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

tgbl-comment/README.md

@@ -19,3 +19,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/tgbl-comment")
 task = relbench.load_task("relbench/tgb/tgbl-comment", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

tgbl-flight/README.md

@@ -19,3 +19,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/tgbl-flight")
 task = relbench.load_task("relbench/tgb/tgbl-flight", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

tgbl-review-v2/README.md

@@ -19,3 +19,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/tgbl-review-v2")
 task = relbench.load_task("relbench/tgb/tgbl-review-v2", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

tgbl-review/README.md

@@ -19,3 +19,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/tgbl-review")
 task = relbench.load_task("relbench/tgb/tgbl-review", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

tgbl-wiki-v2/README.md

@@ -19,3 +19,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/tgbl-wiki-v2")
 task = relbench.load_task("relbench/tgb/tgbl-wiki-v2", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

tgbl-wiki/README.md

@@ -19,3 +19,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/tgbl-wiki")
 task = relbench.load_task("relbench/tgb/tgbl-wiki", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

tgbn-trade/README.md

@@ -19,3 +19,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/tgbn-trade")
 task = relbench.load_task("relbench/tgb/tgbn-trade", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

thgl-forum/README.md

@@ -20,3 +20,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/thgl-forum")
 task = relbench.load_task("relbench/tgb/thgl-forum", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

thgl-github/README.md

@@ -32,3 +32,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/thgl-github")
 task = relbench.load_task("relbench/tgb/thgl-github", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

thgl-myket/README.md

@@ -20,3 +20,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/thgl-myket")
 task = relbench.load_task("relbench/tgb/thgl-myket", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```

thgl-software/README.md

@@ -32,3 +32,34 @@ import relbench
 ds = relbench.load_dataset("relbench/tgb/thgl-software")
 task = relbench.load_task("relbench/tgb/thgl-software", "<task>")
 ```
+
+## Citation
+
+Original dataset: [Temporal Graph Benchmark (TGB / TGB 2.0)](https://tgb.complexdatalab.com/).
+
+```bibtex
+@inproceedings{huang2023temporal,
+  title     = {Temporal Graph Benchmark for Machine Learning on Temporal Graphs},
+  author    = {Huang, Shenyang and Poursafaei, Farimah and Danovitch, Jacob and Fey, Matthias and Hu, Weihua and Rossi, Emanuele and Leskovec, Jure and Bronstein, Michael and Rabusseau, Guillaume and Rabbany, Reihaneh},
+  booktitle = {Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Datasets and Benchmarks Track},
+  year      = {2023}
+}
+
+@inproceedings{gastinger2024tgb2,
+  title     = {{TGB 2.0}: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs},
+  author    = {Gastinger, Julia and Huang, Shenyang and Galkin, Mikhail and Loghmani, Erfan and Parviz, Ali and Poursafaei, Farimah and Danovitch, Jacob and Rossi, Emanuele and Koutis, Ioannis and Stuckenschmidt, Heiner and Rabbany, Reihaneh and Rabusseau, Guillaume},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```
+
+If you use this dataset as hosted by RelBench, please also cite [RelBench](https://proceedings.neurips.cc/paper_files/paper/2024/hash/25cd345233c65fac1fec0ce61d0f7836-Abstract-Datasets_and_Benchmarks_Track.html):
+
+```bibtex
+@inproceedings{robinson2024relbench,
+  title     = {{RelBench}: A Benchmark for Deep Learning on Relational Databases},
+  author    = {Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan E. and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
+  booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track},
+  year      = {2024}
+}
+```