Update paper link

README.md

@@ -58,12 +58,12 @@ license: cdla-permissive-2.0
 ## Dataset Description
 
 - **Homepage:** [Amazon Science](https://www.amazon.science/publications/cross-lingual-knowledge-distillation-for-answer-sentence-selection-in-low-resource-languages)
-- **Paper:** [Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages](https://arxiv.org/abs/2305.16302)
+- **Paper:** [Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages](https://aclanthology.org/2023.findings-acl.885/)
 - **Point of Contact:** [Yoshitomo Matsubara]([email protected])
 
 ### Dataset Summary
 
-***Xtr-WikiQA*** is an Answer Sentence Selection (AS2) dataset in 9 non-English languages, proposed in our paper accepted at ACL 2023 (Findings): **Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages**.
+***Xtr-WikiQA*** is an Answer Sentence Selection (AS2) dataset in 9 non-English languages, proposed in our paper accepted at ACL 2023 (Findings): [**Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages**](https://aclanthology.org/2023.findings-acl.885/).
 This dataset is based on an English AS2 dataset, WikiQA ([Original](https://msropendata.com/datasets/21032bb1-88bd-4656-9570-3172ae1757f0), [Hugging Face](https://huggingface.co/datasets/wiki_qa)).
 For translations, we used [Amazon Translate](https://aws.amazon.com/translate/).
 
@@ -142,11 +142,12 @@ The source of Xtr-WikiQA dataset is [WikiQA](https://msropendata.com/datasets/21
 
 ### Citation Information
 
-```
-@article{gupta2023cross-lingual,
-  title={Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages},
+```bibtex
+@inproceedings{gupta2023cross-lingual,
+  title={{Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages}},
   author={Gupta, Shivanshu and Matsubara, Yoshitomo and Chadha, Ankit and Moschitti, Alessandro},
-  journal={arXiv preprint arXiv:2305.16302},
+  booktitle={Findings of the Association for Computational Linguistics: ACL 2023},
+  pages={14078--14092},
   year={2023}
 }
 ```