Update README.md

README.md

@@ -7,9 +7,11 @@ size_categories:
 - 1K<n<10K
 tags:
 - RAG
+- ConvRAG
 - conversational QA
 - multi-turn QA
 - QA with context
+- evaluation
 configs:
 - config_name: coqa
   data_files:
@@ -110,7 +112,17 @@ The ConvRAG are built on and derived from existing datasets. We refer users to t
 Zihan Liu (zihanl@nvidia.com), Wei Ping (wping@nvidia.com)
 
 ## Citation
-If you evaluate using ConvRAG, please cite all the datasets you use.
+<pre>
+@article{liu2024chatqa,
+  title={ChatQA: Building GPT-4 Level Conversational QA Models},
+  author={Liu, Zihan and Ping, Wei and Roy, Rajarshi and Xu, Peng and Lee, Chankyu and Shoeybi, Mohammad and Catanzaro, Bryan},
+  journal={arXiv preprint arXiv:2401.10225},
+  year={2024}}
+</pre>
+
+
+## Acknowledgement
+We would like to give credits to all the works constructing the datasets we use for evaluating ChatQA. If you use these resources, please also cite all the datasets you use.
 <pre>
 @inproceedings{feng2020doc2dial,
   title={doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset},
@@ -172,9 +184,4 @@ If you evaluate using ConvRAG, please cite all the datasets you use.
   journal={Transactions of the Association for Computational Linguistics},
   year={2023}
 }
-@article{liu2024chatqa,
-  title={ChatQA: Building GPT-4 Level Conversational QA Models},
-  author={Liu, Zihan and Ping, Wei and Roy, Rajarshi and Xu, Peng and Lee, Chankyu and Shoeybi, Mohammad and Catanzaro, Bryan},
-  journal={arXiv preprint arXiv:2401.10225},
-  year={2024}}
 </pre>