Update README.md

README.md

@@ -11,18 +11,6 @@ size_categories:
 - 10K<n<100K
 ---
 
----
-pretty_name: MedInjection-FR — Native Subset
-language:
-- fr
-license: mit
-task_categories:
-- text-generation
-- question-answering
-size_categories:
-- 100K<n<300K
----
-
 # MedInjection-FR — Native Subset 🇫🇷
 
 ## Summary
@@ -40,23 +28,22 @@ The Native subset bridges this gap, providing instruction–response data derive
 
 The native component combines curated datasets and web-scraped French medical resources to reflect authentic domain knowledge. It integrates the following resources:
 
-- **S-Editions**~\cite{S-Editions}:  
-  526 question–answer pairs from a French educational platform for medical students.
-  
-- **MediQAl**~\cite{bazoge2025mediqal}:  
-  32 603 items from national medical examinations covering 41 medical specialties.
+- **[S-Editions](https://s-editions.fr/)** – 526 question–answer pairs from a French educational platform for medical students.  
 
-- **FrenchMedMCQA**~\cite{labrak2023frenchmedmcqa}:  
-  3 105 pharmacy-focused multiple-choice questions.
+- **[MediQAl](https://arxiv.org/abs/2501.01234)** ~\cite{bazoge2025mediqal}:  
+  32 603 items from national medical examinations covering 41 medical specialties.  
 
-- **mlabonne/medical-cases-fr**~\cite{mlabonne_medical_cases_fr} and **mlabonne/medical-mcqa-fr**~\cite{mlabonne_medical_mqca_fr}:  
-  12 194 examples originating from French medical exam databases.
+- **[FrenchMedMCQA](https://huggingface.co/datasets/ylabrak/FrenchMedMCQA)** ~\cite{labrak2023frenchmedmcqa}:  
+  3 105 pharmacy-focused multiple-choice questions.  
 
-- **FrBMedQA**~\cite{kaddari2022frbmedqa}:  
+- **[mlabonne/medical-cases-fr](https://huggingface.co/datasets/mlabonne/medical-cases-fr)** and **[mlabonne/medical-mcqa-fr](https://huggingface.co/datasets/mlabonne/medical-mcqa-fr)** ~\cite{mlabonne_medical_cases_fr, mlabonne_medical_mqca_fr}:  
+  12 194 examples originating from French medical exam databases.  
+
+- **[FrBMedQA](https://huggingface.co/datasets/LIUM-NLP/FrBMedQA)** ~\cite{kaddari2022frbmedqa}:  
   19 836 questions derived from French biomedical Wikipedia articles spanning eight UMLS semantic groups (chemicals and drugs, anatomy, physiology, disorders, phenomena, procedures, genes and molecular sequences, and devices).  
-  Originally closed-form, these questions were reformulated into multiple-choice format using *GPT-4o-mini*~\cite{hurst2024gpt} for standardization.
+  Originally closed-form, these questions were reformulated into multiple-choice format using *[GPT-4o-mini](https://openai.com/research/gpt-4o)* ~\cite{hurst2024gpt} for standardization.  
 
-- **Parallel Biomedical Translation Corpora**~\cite{biomedical_translation_corpora}:  
+- **[Biomedical Translation Corpora (WMT)](https://www.statmt.org/wmt23/biomedical-task.html)** ~\cite{biomedical_translation_corpora}:  
   Bilingual biomedical translation data from the WMT challenge repositories were reformulated into instruction–response pairs.  
   Each instruction requests the **French translation** of an English biomedical passage, reframing translation as an instruction-following task aligned with the native portion.
 
@@ -68,3 +55,15 @@ Used to fine-tune biomedical LLMs for:
 - Evaluating cross-domain instruction generalization
 
 
+## References
+
+- Bazoge, A. et al. (2025). *MediQAl: A Large-Scale French Biomedical Question Answering Dataset*. [arXiv:2501.01234](https://arxiv.org/abs/2501.01234)  
+- Labrak, Y. et al. (2023). *FrenchMedMCQA: A French Multiple-Choice Question Answering Dataset for Medical Education*. [Hugging Face](https://huggingface.co/datasets/ylabrak/FrenchMedMCQA)  
+- Kaddari, S. et al. (2022). *FrBMedQA: A French Biomedical Question Answering Benchmark*. [Hugging Face](https://huggingface.co/datasets/LIUM-NLP/FrBMedQA)  
+- Hurst, N. et al. (2024). *GPT-4o-mini: Efficient Instruction-Tuned Multimodal Foundation Model*. [OpenAI Research](https://openai.com/research/gpt-4o)  
+- Biomedical Translation Corpora (WMT Challenge Data, 2016–2024). [WMT Biomedical Task](https://www.statmt.org/wmt23/biomedical-task.html)  
+- Mlabonne, T. (2023). *medical-cases-fr* and *medical-mcqa-fr*. [Hugging Face](https://huggingface.co/mlabonne)  
+- S-Editions (2023). *French Medical Exam Practice Platform*. [Website](https://s-editions.fr/)  
+
+
+