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README.md

@@ -1,29 +1,14 @@
 ---
-license: cc-by-4.0
-task_categories:
-- summarization
 language:
 - en
+license: cc-by-4.0
 size_categories:
 - n<1K
----
----
-license: apache-2.0
 task_categories:
 - summarization
-language:
-- en
-tags:
-- biomedical
-- health
-- NLP
-- summarization
-- LLM
-size_categories:
-- 1K<n<10K
 ---
 
-PlainFact-summary is a high-quality human-annotated dataset designed for Plain Language Summarization tasks, along with [PlainQAFact](https://github.com/zhiwenyou103/PlainQAFact) factuality evaluation framework. It is collected from the [Cochrane database](https://www.cochranelibrary.com/) sampled from CELLS dataset ([Guo et al., 2024](https://doi.org/10.1016/j.jbi.2023.104580)). 
+PlainFact-summary is a high-quality human-annotated dataset designed for Plain Language Summarization tasks, along with [PlainQAFact](https://github.com/zhiwenyou103/PlainQAFact) factuality evaluation framework, as described in [PlainQAFact: Automatic Factuality Evaluation Metric for Biomedical Plain Language Summaries Generation](https://huggingface.co/papers/2503.08890). It is collected from the [Cochrane database](https://www.cochranelibrary.com/) sampled from CELLS dataset ([Guo et al., 2024](https://doi.org/10.1016/j.jbi.2023.104580)). 
 
 We also provided a sentence-level version [PlainFact](https://huggingface.co/datasets/uzw/PlainFact) that split the summaries into sentences with fine-grained explanation annotations. In total, we have 200 plain language summary-abstract pairs.