Update README.md

README.md

@@ -8,7 +8,7 @@ In-BoXBART
 An instruction-based unified model for performing various biomedical tasks.
 
 You may want to check out 
-* Our paper (NAACL 2022 Findings): [In-BoXBART: Get Instructions into Biomedical Multi-Task Learning](https://arxiv.org/abs/2204.07600)
+* Our paper (NAACL 2022 Findings): [In-BoXBART: Get Instructions into Biomedical Multi-Task Learning](https://aclanthology.org/2022.findings-naacl.10/)
 * GitHub: [Click Here](https://github.com/Mihir3009/In-BoXBART)
 
 This work explores the impact of instructional prompts on biomedical Multi-Task Learning. We introduce the BoX, a collection of 32 instruction tasks for Biomedical NLP across (X) various categories. Using this meta-dataset, we propose a unified model termed In-BoXBART, that can jointly learn all tasks of the BoX without any task-specific modules. To the best of our knowledge, this is the first attempt to
@@ -37,10 +37,21 @@ BibTeX Entry and Citation Info
 If you are using our model, please cite our paper:
 
 ```bibtex
-@article{parmar2022boxbart,
-  title={{In-BoXBART: Get Instructions into Biomedical Multi-Task Learning}},
-  author={Parmar, Mihir and Mishra, Swaroop and Purohit, Mirali and Luo, Man and Murad, M Hassan and Baral, Chitta},
-  journal={NAACL 2022 Findings},
-  year={2022}
+@inproceedings{parmar-etal-2022-boxbart,
+    title = "In-{B}o{XBART}: Get Instructions into Biomedical Multi-Task Learning",
+    author = "Parmar, Mihir  and
+      Mishra, Swaroop  and
+      Purohit, Mirali  and
+      Luo, Man  and
+      Mohammad, Murad  and
+      Baral, Chitta",
+    booktitle = "Findings of the Association for Computational Linguistics: NAACL 2022",
+    month = jul,
+    year = "2022",
+    address = "Seattle, United States",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2022.findings-naacl.10",
+    doi = "10.18653/v1/2022.findings-naacl.10",
+    pages = "112--128",
 }
 ```