Docs: Update project description and links

README.md

@@ -8,6 +8,8 @@ tags:
 - finance
 - 10k
 - edgar
+- agent
+- benchmark
 size_categories:
 - 1M<n<10M
 configs:
@@ -53,30 +55,36 @@ configs:
     path: data/table_comments/table_comments.parquet
 ---
 
-# DDRBench 10K Financial Database
+# DDRBench: Deep Data Research Benchmark
 
-This dataset contains the structured SQLite database tables used in the **DDRBench 10K** evaluation task, converted to Parquet format.
+[**📊 Leaderboard & Demo**](https://huggingface.co/spaces/thinkwee/DDR_Bench) | [**📄 Paper (Arxiv)**](https://arxiv.org/html/2602.02039v1)
 
-## Structure
-The dataset is split into multiple configurations, each representing a table from the original database:
+## Overview
+**DDRBench (Deep Data Research Benchmark)** is a comprehensive evaluation framework designed to assess the capabilities of Large Language Model (LLM) agents in performing complex, multi-turn data research and reasoning tasks. Unlike traditional Q&A benchmarks, DDRBench focuses on scenarios requiring deep interaction with structured databases, tool usage, and long-context reasoning.
 
-- **companies**: Master table of companies (CIK, Name, etc.).
-- **financial_facts**: The core financial data (5M+ rows).
-- **filings**: Metadata about SEC filings.
-- **company_addresses**: Address information.
-- **company_tickers**: Ticker symbol mappings.
-- **table/column_documentation**: Metadata and comments explaining the schema.
+This dataset repository specifically hosts the **10-K Financial Database**, a core component of the DDRBench suite. It contains structured financial data extracted from SEC 10-K filings, enabling agents to answer intricate financial questions that mimic real-world analyst workflows.
+
+## Dataset Structure
+The dataset is organized into multiple configurations (subsets), representing different tables from the underlying SQLite database:
+
+*   **`financial_facts`**: The primary table containing over 5 million financial metrics (US-GAAP, IFRS) with values, units, and fiscal periods.
+*   **`companies`**: Registry of companies with CIK, names, and SIC codes.
+*   **`filings`**: Metadata for the SEC filings source documents.
+*   **`company_addresses`** & **`company_tickers`**: Geographic and market identification data.
+*   **`table_documentation`** & **`column_documentation`**: Meta-information describing the database schema to the agents.
 
 ## Usage
 
-To load a specific table:
+Load specific tables using the `datasets` library:
 
 ```python
 from datasets import load_dataset
 
-# Load the 'companies' table
-ds_companies = load_dataset("thinkwee/DDRBench_10K", "companies")
+# Load the main financial facts table
+financial_facts = load_dataset("thinkwee/DDRBench_10K", "financial_facts")
 
-# Load the main financial facts
-ds_facts = load_dataset("thinkwee/DDRBench_10K", "financial_facts")
+# Load company information
+companies = load_dataset("thinkwee/DDRBench_10K", "companies")
 ```
+
+For agent trajectories and evaluation logs, please refer to the [DDRBench Trajectory Dataset](https://huggingface.co/datasets/thinkwee/DDRBench_10K_trajectory).