Update README.md

README.md

@@ -67,9 +67,7 @@ size_categories:
 
 This repository hosts the **Korean Canonical Legal Benchmark (KCL)** datasets.  
 
-Evaluation Code Repository [![Github](https://img.shields.io/badge/GitHub-KCL-blue?style=flat&logo=github)](https://github.com/lbox-kr/kcl)
-
-For more information, please refer to our paper [![Paper](https://img.shields.io/badge/arXiv-1234.1234-red?style=flat&logo=arxiv&logoColor=red)](https://arxiv.org/abs/1234.1234)
+[![Github](https://img.shields.io/badge/GitHub-KCL-blue?style=flat&logo=github)](https://github.com/lbox-kr/kcl) [![Paper](https://img.shields.io/badge/arXiv-1234.1234-red?style=flat&logo=arxiv&logoColor=red)](https://arxiv.org/abs/1234.1234)
 
 ## Why KCL?
 
@@ -81,6 +79,8 @@ KCL supports two complementary evaluation axes:
 
 For essay questions, KCL further offers **instance-level rubrics** to enable **LLM-as-a-Judge** automated scoring.
 
+For more information, please refer to our paper 
+
 #### Intended Uses
  - Separating knowledge vs. reasoning by comparing vanilla and with-precedent settings.
  - Legal RAG research using question-aligned gold precedents to establish retriever/reader upper bounds.
@@ -109,11 +109,11 @@ kcl_mcqa = load_dataset("lbox/kcl", "kcl_mcqa", split="test")
 
 ## Dataset Fields
 
-meta: Metadata such as exam year, subject, and question id.
-question: The full prompt presented to models.
-rubrics: Instance-level grading rubrics for automated evaluation.
-score: The original point value assigned in the official bar exam (reflecting difficulty).
-supporting\_precedents: Question-aligned court decisions required to solve the problem.
+ - meta: Metadata such as exam year, subject, and question id.
+ - question: The full prompt presented to models.
+ - rubrics: Instance-level grading rubrics for automated evaluation.
+ - score: The original point value assigned in the official bar exam (reflecting difficulty).
+ - supporting\_precedents: Question-aligned court decisions required to solve the problem.
 
 #### Results
 
@@ -123,11 +123,11 @@ supporting\_precedents: Question-aligned court decisions required to solve the p
 
 ### Dataset Fields
 
-meta: Metadata about the source exam item.
-question: The full prompt presented to models.
-A–E: Five answer options.
-label: The gold answer option letter (one of 'A'|'B'|'C'|'D'|'E').
-supporting\_precedents: Question-aligned court decisions required to solve the problem.
+ - meta: Metadata about the source exam item.
+ - question: The full prompt presented to models.
+ - A–E: Five answer options.
+ - label: The gold answer option letter (one of 'A'|'B'|'C'|'D'|'E').
+ - supporting\_precedents: Question-aligned court decisions required to solve the problem.
 
 #### Results