update README example

README.md

@@ -141,40 +141,21 @@ Contains enhanced citations with full paper metadata and content:
 from datasets import load_dataset
 
 # Load papers dataset
-papers = load_dataset("deepscholar-bench/DeepScholarBench", name="papers", trust_remote_code=True)["train"]
+papers = load_dataset("deepscholar-bench/DeepScholarBench", name="papers")["train"]
 print(f"Loaded {len(papers)} papers")
 
 # Load citations dataset  
-citations = load_dataset("deepscholar-bench/DeepScholarBench", name="citations", trust_remote_code=True)["train"]
+citations = load_dataset("deepscholar-bench/DeepScholarBench", name="citations")["train"]
 print(f"Loaded {len(citations)} citations")
 
 # Load important citations with enhanced metadata
-important_citations = load_dataset("deepscholar-bench/DeepScholarBench", name="important_citations", trust_remote_code=True)["train"]
+important_citations = load_dataset("deepscholar-bench/DeepScholarBench", name="important_citations")["train"]
 print(f"Loaded {len(important_citations)} important citations")
 
 # Convert to pandas for analysis
 papers_df = papers.to_pandas()
 citations_df = citations.to_pandas()
-```
-
-**Note**: This dataset uses a custom loading script, so you need to include `trust_remote_code=True` when loading.
-
-### Alternative: Direct CSV Loading
-
-```python
-import pandas as pd
-
-# Load papers dataset
-papers_df = pd.read_csv('papers_with_related_works.csv')
-print(f"Loaded {len(papers_df)} papers")
-
-# Load citations dataset
-citations_df = pd.read_csv('recovered_citations.csv')
-print(f"Loaded {len(citations_df)} citations")
-
-# Load important citations
-important_citations_df = pd.read_csv('important_citations.csv')
-print(f"Loaded {len(important_citations_df)} important citations")
+important_citations_df = important_citations.to_pandas()
 ```
 
 ### Example: Extract Related Works for a Paper
@@ -194,7 +175,7 @@ print(f"Number of citations: {len(paper_citations)}")
 
 ```python
 # Load important citations (enhanced with paper metadata)
-important_citations = load_dataset("deepscholar-bench/DeepScholarBench", name="important_citations", trust_remote_code=True)["train"]
+important_citations = load_dataset("deepscholar-bench/DeepScholarBench", name="important_citations")["train"]
 
 # This configuration includes both citation data AND the parent paper information
 sample = important_citations[0]