Update README

README.md

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 # Dataset Card for EffiBench-X
 
-**EffiBench-X** is the first multi-language benchmark designed specifically to evaluate the efficiency of LLM-generated code across six programming languages: Python, C++, Java, JavaScript, Ruby, and Golang. The dataset comprises 623 competitive programming problems sourced from platforms released after October 2023 to mitigate data contamination, paired with human expert solutions as efficiency baselines.
+**EffiBench-X** is the first multi-language benchmark designed specifically to evaluate the efficiency of LLM-generated code across six programming languages: Python, C++, Java, JavaScript, Ruby, and Golang. The dataset comprises 623 competitive programming problems paired with human expert solutions as efficiency baselines.
 
 ## Dataset Details
 
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 EffiBench-X addresses critical limitations in existing code generation benchmarks by providing:
 - **Multi-language evaluation** across Python, C++, Java, JavaScript, Ruby, and Golang
 - **Efficiency-focused metrics** including execution time, memory peak, and memory integral
-- **Recent competitive programming problems** (post-October 2023) to avoid data contamination
 - **Human expert baselines** for reliable efficiency comparison
 
 - **Curated by:** Yuhao Qing, Boyu Zhu, Mingzhe Du, Zhijiang Guo, Terry Yue Zhuo, Qianru Zhang, Jie M. Zhang, Heming Cui, Siu-Ming Yiu, Dong Huang, See-Kiong Ng, Luu Anh Tuan
@@ -249,7 +248,7 @@ Key fields per record include:
   - `generated_tests`: serialized tests produced by the generator
   - `test_runners`: language-keyed runner templates for executing solutions
 
-All problems are from competitive programming platforms, with release dates after October 2023 to minimize data contamination.
+All problems are from competitive programming platforms.
 
 ## Dataset Creation
 
@@ -265,7 +264,7 @@ Existing code generation benchmarks primarily focus on functional correctness wi
 
 #### Data Collection and Processing
 
-Problems are curated from competitive programming platforms released after October 2023 to minimize data contamination. Each problem includes:
+Problems are curated from competitive programming platforms. Each problem includes:
 - Human expert solutions verified for correctness and efficiency
 - 100 programmatically generated test cases
 - Test runners and evaluators for automated assessment