Update README.md

README.md

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 ## Summary
 
 The **Translated** component of **MedInjection-FR** adapts large-scale **English biomedical instruction datasets** into French through high-quality automatic translation.  
-It represents the most extensive part of the collection, comprising **418 061 instruction–response pairs**, and provides a bridge between English biomedical resources and French medical instruction tuning.
+It represents the most extensive part of the collection, comprising **416 401 instruction–response pairs**, and provides a bridge between English biomedical resources and French medical instruction tuning.
 
 This subset was designed to ensure **broad domain coverage** while maintaining **semantic and linguistic fidelity**, enabling robust cross-lingual transfer and comparative evaluation between native, synthetic, and translated supervision sources.
 
 ## Motivation
 
 The scarcity of large-scale French biomedical instruction data limits the capacity of LLMs to generalize across complex medical domains.  
-To address this, the Translated subset leverages **trusted English benchmarks**—spanning medicine, biology, psychology, and clinical knowledge—and systematically translates them into French while preserving the structure of instruction–response pairs.
+To address this, the Translated subset leverages **trusted English benchmarks** spanning medicine, biology, psychology, and clinical knowledge and systematically translates them into French while preserving the structure of instruction–response pairs.
 
 This allows for rigorous experiments on **cross-lingual instruction adaptation**, complementing the native and synthetic subsets of MedInjection-FR.
 
 ## Composition
 
 To expand data coverage while maintaining linguistic fidelity, a large collection of **English biomedical instruction datasets** was translated into French using **[Gemini 2.0 Flash](https://blog.google/products/gemini/google-gemini-2/)** and **[GPT-4o-mini](https://openai.com/research/gpt-4o)**.  
-The translated component comprises **418 061 instruction–response pairs** derived from several established English resources:
+The translated component comprises **416 401 instruction–response pairs** derived from several established English resources:
 
 - **[MedQA](https://arxiv.org/abs/2009.13081)** – medical board–style multiple-choice QA.  
 - **[PubMedQA](https://aclanthology.org/D19-1259/)**  – factoid biomedical QA from PubMed abstracts.  
@@ -40,7 +40,7 @@ The translated component comprises **418 061 instruction–response pairs** deri
 - **[MMLU-PRO](https://arxiv.org/abs/2406.01574)**  – professional-level QA across psychology, biology, and health domains.  
 - **[MedXpertQA](https://arxiv.org/abs/2501.18362)**  – clinical reasoning dataset focusing on multi-hop and expert-level diagnostic questions.
 
-To assess translation quality, outputs were evaluated using **BLEU** and **COMET** on the **[WMT 2024 Biomedical Translation Task](https://www.statmt.org/wmt24/biomedical-task.html)** corpus \cite{neves-etal-2024-findings}.  
+To assess translation quality, outputs were evaluated using **BLEU** and **COMET** on the **[WMT 2024 Biomedical Translation Task](https://github.com/biomedical-translation-corpora/corpora)** corpus.  
 Both *Gemini 2.0 Flash* and *GPT-4o-mini* achieved results comparable to the **best WMT 2024 system**, indicating that the Translated subset maintains high semantic fidelity and linguistic quality suitable for French biomedical instruction tuning.
 
 ## Use