Update README.md

README.md

@@ -46,7 +46,7 @@ We report **Normalized Discounted Cumulative Gain (NDCG)** scores, which measure
 - **Avg. NDCG**: Average of NDCG@1, @3, @5, and @10 across all benchmark datasets.  
 - **NDCG@k**: Relevance quality of the top-*k* retrieved results.
  
-#### Korean Retrieval Benchmarks
+#### 7 Datasets of MTEB (Korean)
 Our model, **telepix/PIXIE-Rune-Preview**, achieves state-of-the-art performance across most metrics and benchmarks, demonstrating strong generalization across domains such as multi-hop QA, long-document retrieval, public health, and e-commerce.
 
 | Model Name | # params | Avg. NDCG | NDCG@1 | NDCG@3 | NDCG@5 | NDCG@10 |
@@ -78,7 +78,7 @@ Descriptions of the benchmark datasets used for evaluation are as follows:
 - **XPQARetrieval**  
   A real-world dataset constructed from user queries and relevant product documents in a Korean e-commerce platform.
 
-#### English Retrieval Benchmarks
+#### 7 Datasets of BEIR (English)
 Our model, **telepix/PIXIE-Rune-Preview**, achieves strong performance on a wide range of tasks, including fact verification, multi-hop question answering, financial QA, and scientific document retrieval, demonstrating competitive generalization across diverse domains.
  
 | Model Name | # params | Avg. NDCG | NDCG@1 | NDCG@3 | NDCG@5 | NDCG@10 |