fix

lotus_deep_research.py → DeepScholarBench.py

@@ -1,5 +1,5 @@
 """
-Lotus Deep Research Dataset: Academic papers with extracted related works sections and recovered citations.
+DeepScholarBench: Academic papers with extracted related works sections and recovered citations.
 
 This dataset contains academic papers from ArXiv with their related works sections and recovered citations,
 providing a rich resource for research generation and citation analysis tasks.
@@ -24,7 +24,7 @@ _CITATION = """\
       title={DeepScholar-Bench: A Live Benchmark and Automated Evaluation for Generative Research Synthesis}, 
       author={Liana Patel and Negar Arabzadeh and Harshit Gupta and Ankita Sundar and Ion Stoica and Matei Zaharia and Carlos Guestrin},
       year={2025},
-      eprint={2508.20033},
+      eprint={2412.19698},
       archivePrefix={arXiv},
       primaryClass={cs.CL},
       url={https://arxiv.org/abs/2508.20033}, 
@@ -42,18 +42,18 @@ _URLS = {
 }
 
 
-class LotusDeepResearchConfig(datasets.BuilderConfig):
-    """BuilderConfig for LotusDeepResearch dataset."""
+class DeepScholarBenchConfig(datasets.BuilderConfig):
+    """BuilderConfig for DeepScholarBench dataset."""
 
     def __init__(self, name: str, description: str, **kwargs):
-        """BuilderConfig for LotusDeepResearch.
+        """BuilderConfig for DeepScholarBench.
         
         Args:
             name: Configuration name
             description: Description of this configuration
             **kwargs: Additional keyword arguments
         """
-        super(LotusDeepResearchConfig, self).__init__(
+        super(DeepScholarBenchConfig, self).__init__(
             name=name,
             description=description,
             version=datasets.Version("1.0.0"),
@@ -61,31 +61,31 @@ class LotusDeepResearchConfig(datasets.BuilderConfig):
         )
 
 
-class LotusDeepResearch(datasets.GeneratorBasedBuilder):
-    """Lotus Deep Research dataset."""
+class DeepScholarBench(datasets.GeneratorBasedBuilder):
+    """DeepScholarBench dataset."""
 
     VERSION = datasets.Version("1.0.0")
 
     BUILDER_CONFIGS = [
-        LotusDeepResearchConfig(
+        DeepScholarBenchConfig(
             name="papers",
             description="Academic papers with extracted related works sections (63 papers)",
         ),
-        LotusDeepResearchConfig(
+        DeepScholarBenchConfig(
             name="citations", 
             description="Recovered citations with metadata (1630 citations)",
         ),
-        LotusDeepResearchConfig(
+        DeepScholarBenchConfig(
             name="important_citations",
-            description="Important citations with metadata (1050 citations)",
+            description="Important citations with enhanced metadata (1050 citations)",
         ),
-        LotusDeepResearchConfig(
+        DeepScholarBenchConfig(
             name="full",
-            description="Complete dataset with both papers and citations",
+            description="Complete dataset with papers, citations, and important citations",
         ),
     ]
 
-    DEFAULT_CONFIG_NAME = "full"
+    DEFAULT_CONFIG_NAME = "papers"
 
     def _info(self) -> datasets.DatasetInfo:
         """Return the dataset info."""
@@ -161,74 +161,8 @@ class LotusDeepResearch(datasets.GeneratorBasedBuilder):
             })
         else:  # full config
             features = datasets.Features({
-                # Papers features
-                "papers": datasets.Sequence({
-                    "arxiv_id": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "authors": datasets.Value("string"),
-                    "abstract": datasets.Value("string"),
-                    "categories": datasets.Value("string"),
-                    "published_date": datasets.Value("string"),
-                    "updated_date": datasets.Value("string"),
-                    "abs_url": datasets.Value("string"),
-                    "arxiv_link": datasets.Value("string"),
-                    "publication_date": datasets.Value("string"),
-                    "raw_latex_related_works": datasets.Value("string"),
-                    "clean_latex_related_works": datasets.Value("string"),
-                    "pdf_related_works": datasets.Value("string"),
-                }),
-                # Citations features
-                "citations": datasets.Sequence({
-                    "parent_paper_title": datasets.Value("string"),
-                    "parent_paper_arxiv_id": datasets.Value("string"),
-                    "citation_shorthand": datasets.Value("string"),
-                    "raw_citation_text": datasets.Value("string"),
-                    "cited_paper_title": datasets.Value("string"),
-                    "cited_paper_arxiv_link": datasets.Value("string"),
-                    "cited_paper_abstract": datasets.Value("string"),
-                    "has_metadata": datasets.Value("bool"),
-                    "is_arxiv_paper": datasets.Value("bool"),
-                    "bib_paper_authors": datasets.Value("string"),
-                    "bib_paper_year": datasets.Value("float32"),
-                    "bib_paper_month": datasets.Value("string"),
-                    "bib_paper_url": datasets.Value("string"),
-                    "bib_paper_doi": datasets.Value("string"),
-                    "bib_paper_journal": datasets.Value("string"),
-                    "original_title": datasets.Value("string"),
-                    "search_res_title": datasets.Value("string"),
-                    "search_res_url": datasets.Value("string"),
-                    "search_res_content": datasets.Value("string"),
-                }),
-                "important_citations": datasets.Sequence({
-                    "parent_paper_title": datasets.Value("string"),
-                    "parent_paper_arxiv_id": datasets.Value("string"),
-                    "citation_shorthand": datasets.Value("string"),
-                    "raw_citation_text": datasets.Value("string"),
-                    "cited_paper_title": datasets.Value("string"),
-                    "cited_paper_arxiv_link": datasets.Value("string"),
-                    "cited_paper_abstract": datasets.Value("string"),
-                    "has_metadata": datasets.Value("bool"),
-                    "is_arxiv_paper": datasets.Value("bool"),
-                    "cited_paper_authors": datasets.Value("string"),
-                    "bib_paper_year": datasets.Value("float32"),
-                    "bib_paper_month": datasets.Value("string"),
-                    "bib_paper_url": datasets.Value("string"),
-                    "bib_paper_doi": datasets.Value("string"),
-                    "bib_paper_journal": datasets.Value("string"),
-                    "original_title": datasets.Value("string"),
-                    "search_res_title": datasets.Value("string"),
-                    "search_res_url": datasets.Value("string"),
-                    "search_res_content": datasets.Value("string"),
-                    "arxiv_id": datasets.Value("string"),
-                    "arxiv_link": datasets.Value("string"),
-                    "publication_date": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "abstract": datasets.Value("string"),
-                    "raw_latex_related_works": datasets.Value("string"),
-                    "related_work_section": datasets.Value("string"),
-                    "pdf_related_works": datasets.Value("string"),
-                    "cited_paper_content": datasets.Value("string"),
-                })
+                "split": datasets.Value("string"),
+                "data": datasets.Value("string"),  # JSON encoded data
             })
 
         return datasets.DatasetInfo(
@@ -370,6 +304,7 @@ class LotusDeepResearch(datasets.GeneratorBasedBuilder):
                         "search_res_url": row.get("search_res_url", ""),
                         "search_res_content": row.get("search_res_content", ""),
                     }
+
         elif split == "important_citations":
             with open(filepath, encoding="utf-8") as f:
                 reader = csv.DictReader(f)
@@ -384,7 +319,7 @@ class LotusDeepResearch(datasets.GeneratorBasedBuilder):
                         "cited_paper_abstract": row.get("cited_paper_abstract", ""),
                         "has_metadata": _safe_bool_convert(row.get("has_metadata", "False")),
                         "is_arxiv_paper": _safe_bool_convert(row.get("is_arxiv_paper", "False")),
-                        "bib_paper_authors": row.get("bib_paper_authors", ""),
+                        "cited_paper_authors": row.get("cited_paper_authors", ""),
                         "bib_paper_year": _safe_float_convert(row.get("bib_paper_year", "")),
                         "bib_paper_month": row.get("bib_paper_month", ""),
                         "bib_paper_url": row.get("bib_paper_url", ""),
@@ -394,4 +329,13 @@ class LotusDeepResearch(datasets.GeneratorBasedBuilder):
                         "search_res_title": row.get("search_res_title", ""),
                         "search_res_url": row.get("search_res_url", ""),
                         "search_res_content": row.get("search_res_content", ""),
-                    }
+                        "arxiv_id": row.get("arxiv_id", ""),
+                        "arxiv_link": row.get("arxiv_link", ""),
+                        "publication_date": row.get("publication_date", ""),
+                        "title": row.get("title", ""),
+                        "abstract": row.get("abstract", ""),
+                        "raw_latex_related_works": row.get("raw_latex_related_works", ""),
+                        "related_work_section": row.get("related_work_section", ""),
+                        "pdf_related_works": row.get("pdf_related_works", ""),
+                        "cited_paper_content": row.get("cited_paper_content", ""),
+                    }

README.md

@@ -7,15 +7,25 @@ language:
 - en
 tags:
 - code
-pretty_name: LOTUS Scraped Data (2025/06/07)
+pretty_name: DeepScholarBench Dataset
 size_categories:
 - 1K<n<10K
+configs:
+- config_name: papers
+  data_files: "papers_with_related_works.csv"
+- config_name: citations
+  data_files: "recovered_citations.csv" 
+- config_name: important_citations
+  data_files: "important_citations.csv"
+- config_name: full
+  data_files: ["papers_with_related_works.csv", "recovered_citations.csv", "important_citations.csv"]
 ---
-# Lotus Deep Research Dataset
+# DeepScholarBench Dataset
 
-[![Dataset](https://img.shields.io/badge/Dataset-lotus--data%2FDeepScholarBench-blue)](https://huggingface.co/datasets/lotus-data/DeepScholarBench)
-[![GitHub](https://img.shields.io/badge/GitHub-lotus--deep--research-green)](https://github.com/harshitgupta412/lotus-deep-research)
-[![License](https://img.shields.io/badge/License-MIT-yellow)](https://github.com/harshitgupta412/lotus-deep-research/blob/main/LICENSE)
+[![Dataset](https://img.shields.io/badge/Dataset-deepscholar--bench%2FDeepScholarBench-blue)](https://huggingface.co/datasets/deepscholar-bench/DeepScholarBench)
+[![GitHub](https://img.shields.io/badge/GitHub-deepscholar--bench-green)](https://github.com/guestrin-lab/deepscholar-bench)
+[![License](https://img.shields.io/badge/License-MIT-yellow)](https://github.com/guestrin-lab/deepscholar-bench/blob/main/LICENSE)
+[![Paper](https://img.shields.io/badge/Paper-arXiv%3A2508.20033-red)](https://arxiv.org/abs/2508.20033)
 
 ---
 
@@ -80,23 +90,72 @@ Contains individual citations with recovered metadata:
 | `search_res_url` | URL from search results |
 | `search_res_content` | Content snippet from search results |
 
+### 3. `important_citations.csv` (1,050 citations)
+
+Contains enhanced citations with full paper metadata and content:
+
+| Column | Description |
+|--------|-------------|
+| `parent_paper_title` | Title of the paper containing the citation |
+| `parent_paper_arxiv_id` | ArXiv ID of the parent paper |
+| `citation_shorthand` | Citation key (e.g., "NBERw21340") |
+| `raw_citation_text` | Raw citation text from LaTeX |
+| `cited_paper_title` | Title of the cited paper |
+| `cited_paper_arxiv_link` | ArXiv link if available |
+| `cited_paper_abstract` | Abstract of the cited paper |
+| `has_metadata` | Whether metadata was successfully recovered |
+| `is_arxiv_paper` | Whether the cited paper is from ArXiv |
+| `cited_paper_authors` | Authors of the cited paper |
+| `bib_paper_year` | Publication year |
+| `bib_paper_month` | Publication month |
+| `bib_paper_url` | URL of the cited paper |
+| `bib_paper_doi` | DOI of the cited paper |
+| `bib_paper_journal` | Journal name |
+| `original_title` | Original title from citation metadata |
+| `search_res_title` | Title from search results |
+| `search_res_url` | URL from search results |
+| `search_res_content` | Content snippet from search results |
+| `arxiv_id` | ArXiv ID of the parent paper |
+| `arxiv_link` | ArXiv link of the parent paper |
+| `publication_date` | Publication date of the parent paper |
+| `title` | Title of the parent paper |
+| `abstract` | Abstract of the parent paper |
+| `raw_latex_related_works` | Raw LaTeX related works section |
+| `related_work_section` | Processed related works section |
+| `pdf_related_works` | Related works extracted from PDF |
+| `cited_paper_content` | Full content of the cited paper |
+
+## ⚙️ Dataset Configurations
+
+| Configuration | Description | Files | Records | Use Case |
+|---------------|-------------|--------|---------|----------|
+| `papers` | Academic papers only | `papers_with_related_works.csv` | 63 papers | Research generation, content analysis |
+| `citations` | Citations only | `recovered_citations.csv` | 1,630 citations | Citation analysis, relationship mapping |
+| `important_citations` | Enhanced citations with metadata | `important_citations.csv` | 1,050 citations | Advanced citation analysis, paper-citation linking |
+
 ## 🚀 Quick Start
 
-### Loading the Dataset
+### Loading from Hugging Face Hub (Recommended)
 
 ```python
-import pandas as pd
+from datasets import load_dataset
 
 # Load papers dataset
-papers_df = pd.read_csv('papers_with_related_works.csv')
-print(f"Loaded {len(papers_df)} papers")
+papers = load_dataset("deepscholar-bench/DeepScholarBench", name="papers")["train"]
+print(f"Loaded {len(papers)} papers")
 
-# Load citations dataset
-citations_df = pd.read_csv('citations_with_recovered_res.csv')
-print(f"Loaded {len(citations_df)} citations")
-```
+# Load citations dataset  
+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")["train"]
+print(f"Loaded {len(important_citations)} important citations")
 
+# Convert to pandas for analysis
+papers_df = papers.to_pandas()
+citations_df = citations.to_pandas()
+```
 
 ### Example: Extract Related Works for a Paper
 
@@ -113,13 +172,14 @@ print(f"Number of citations: {len(paper_citations)}")
 
 ## 📈 Dataset Statistics
 
-- **Total Papers**: 67
-- **Total Citations**: 1663
+- **Total Papers**: 63
+- **Total Citations**: 1,630
+- **Important Citations**: 1,050
 - **Date Range**: 2024-2025 (recent papers)
 
 ## 🔧 Data Collection Process
 
-This dataset was created using the [Lotus Deep Research](https://github.com/harshitgupta412/lotus-deep-research) pipeline:
+This dataset was created using the [Lotus Deep Research](https://github.com/guestrin-lab/deepscholar-bench) pipeline:
 
 1. **ArXiv Scraping**: Collected papers by category and date range
 2. **Author Filtering**: Focused on high-impact researchers (h-index ≥ 25)
@@ -129,17 +189,17 @@ This dataset was created using the [Lotus Deep Research](https://github.com/hars
 
 ## 📚 Related Resources
 
-- **[GitHub Repository](https://github.com/harshitgupta412/lotus-deep-research)**: Full source code and documentation
-- **[Data Pipeline](https://github.com/harshitgupta412/lotus-deep-research/tree/main/data_pipeline)**: Tools for collecting similar datasets
-- **[Evaluation Framework](https://github.com/harshitgupta412/lotus-deep-research/tree/main/eval)**: Framework for evaluating research generation systems
+- **[GitHub Repository](https://github.com/guestrin-lab/deepscholar-bench)**: Full source code and documentation
+- **[Data Pipeline](https://github.com/guestrin-lab/deepscholar-bench/tree/main/data_pipeline)**: Tools for collecting similar datasets
+- **[Evaluation Framework](https://github.com/guestrin-lab/deepscholar-bench/tree/main/eval)**: Framework for evaluating research generation systems
 
 ## 🤝 Contributing
 
-We welcome contributions to improve this dataset! Please see the [main repository](https://github.com/harshitgupta412/lotus-deep-research) for contribution guidelines.
+We welcome contributions to improve this dataset! Please see the [main repository](https://github.com/guestrin-lab/deepscholar-bench) for contribution guidelines.
 
 ## 📄 License
 
-This dataset is released under the MIT License. See the [LICENSE](https://github.com/harshitgupta412/lotus-deep-research/blob/main/LICENSE) file for details.
+This dataset is released under the MIT License. See the [LICENSE](https://github.com/guestrin-lab/deepscholar-bench/blob/main/LICENSE) file for details.
 
 ---
 

usage_example.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
-Usage example for the Lotus Deep Research dataset.
+Usage example for the DeepScholarBench dataset.
 
 This shows how to use the dataset builder directly, which is the recommended approach
 for local development and testing.
@@ -13,7 +13,7 @@ from pathlib import Path
 # Add the current directory to Python path
 sys.path.insert(0, str(Path(__file__).parent))
 
-from lotus_deep_research import LotusDeepResearch
+from DeepScholarBench import DeepScholarBench
 import pandas as pd
 
 
@@ -22,7 +22,7 @@ def load_papers_dataset():
     print("Loading papers dataset...")
     
     # Create dataset builder
-    builder = LotusDeepResearch(config_name="papers")
+    builder = DeepScholarBench(config_name="papers")
     
     # Mock download manager for local files
     class MockDownloadManager:
@@ -52,7 +52,7 @@ def load_citations_dataset():
     print("Loading citations dataset...")
     
     # Create dataset builder
-    builder = LotusDeepResearch(config_name="citations")
+    builder = DeepScholarBench(config_name="citations")
     
     # Mock download manager for local files
     class MockDownloadManager:
@@ -82,7 +82,7 @@ def load_important_citations_dataset():
     print("Loading important citations dataset...")
     
     # Create dataset builder
-    builder = LotusDeepResearch(config_name="important_citations")
+    builder = DeepScholarBench(config_name="important_citations")
     
     # Mock download manager for local files
     class MockDownloadManager:
@@ -109,7 +109,7 @@ def load_important_citations_dataset():
 
 def main():
     """Main example function."""
-    print("Lotus Deep Research Dataset - Usage Example")
+    print("DeepScholarBench Dataset - Usage Example")
     print("=" * 50)
     
     # Load datasets