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README.md

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 ### HumanEval-V: A Lightweight Visual Understanding and Reasoning Benchmark for Evaluating LMMs through Coding Tasks
 
-<p align="center"> <a href="">📄 Paper</a> • <a href="https://humaneval-v.github.io">🏠 Home Page</a> • <a href="https://github.com/HumanEval-V/HumanEval-V-Benchmark">💻 GitHub Repository</a> • <a href="https://humaneval-v.github.io/#leaderboard">🏆 Leaderboard</a> • <a href="https://github.com/HumanEval-V/HumanEval-V-Benchmark">🤗 Dataset</a> • <a href="https://huggingface.co/spaces/HumanEval-V/HumanEval-V-Benchmark-Viewer">🤗 Dataset Viewer</a>  </p> 
+<p align="center"> <a href="">📄 Paper</a> • <a href="https://humaneval-v.github.io">🏠 Home Page</a> • <a href="https://github.com/HumanEval-V/HumanEval-V-Benchmark">💻 GitHub Repository</a> • <a href="https://humaneval-v.github.io/#leaderboard">🏆 Leaderboard</a> • <a href="https://huggingface.co/datasets/HumanEval-V/HumanEval-V-Benchmark">🤗 Dataset</a> • <a href="https://huggingface.co/spaces/HumanEval-V/HumanEval-V-Benchmark-Viewer">🤗 Dataset Viewer</a>  </p> 
 
 **HumanEval-V** is a novel and lightweight benchmark designed to evaluate the visual understanding and reasoning capabilities of Large Multimodal Models (LMMs) through coding tasks. The dataset comprises **108 entry-level Python programming challenges**, adapted from platforms like CodeForces and Stack Overflow. Each task includes **visual context that is  indispensable to the problem**, requiring models to perceive, reason, and generate Python code solutions accordingly.