Add library_name and paper link to model card

README.md

@@ -1,20 +1,20 @@
 ---
-license: apache-2.0
 datasets:
 - uzw/PlainFact
 language:
 - en
+license: apache-2.0
 metrics:
 - accuracy
 pipeline_tag: text-classification
+library_name: transformers
 tags:
 - biology
 - medical
 - classification
 ---
 
-> This plain language summary classification model is a part of the [PlainQAFact](https://github.com/zhiwenyou103/PlainQAFact) factuality evaluation framework. 
-
+> This plain language summary classification model is a part of the [PlainQAFact](https://github.com/zhiwenyou103/PlainQAFact) factuality evaluation framework, introduced in the paper [PlainQAFact: Retrieval-augmented Factual Consistency Evaluation Metric for Biomedical Plain Language Summarization](https://huggingface.co/papers/2503.08890).
 
 ## Classify the Input into Either Elaborative Explanation or Simplification
 We fine-tuned [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) model using our curated sentence-level [PlainFact](https://huggingface.co/datasets/uzw/PlainFact) dataset.
@@ -68,7 +68,7 @@ print(f"Confidence scores: {predictions}")
 
 
 ## Citation
-If you use this QG model in your research, please cite with the following BibTex entry:
+If you use this model in your research, please cite with the following BibTex entry:
 ```
 @misc{you2025plainqafactretrievalaugmentedfactualconsistency,
       title={PlainQAFact: Retrieval-augmented Factual Consistency Evaluation Metric for Biomedical Plain Language Summarization},