Update src/about.py

src/about.py

@@ -79,19 +79,16 @@ FlagEval-Embodied Verse is a scientific and comprehensive embodied evaluation to
 We hope to promote a more open ecosystem for embodied model developers to participate and contribute accordingly to the advancement of embodied models. To achieve the goal of fairness, all models are evaluated all models are evaluated under the FlagEvalMM framework using standardized GPUs and a unified environment to ensure fairness.
 
 ## Embodied Verse
-
-| 数据集     | 论文      | 链接      |
-|------------|------------|------------|
-| Where2Place| https://arxiv.org/abs/2406.10721    | https://huggingface.co/datasets/FlagEval/Where2Place    |
-| Blink    | https://arxiv.org/abs/2404.12390    | https://huggingface.co/datasets/BLINK-Benchmark/BLINK    |
-| CVBench   | https://arxiv.org/abs/2406.16860   | https://huggingface.co/datasets/nyu-visionx/CV-Bench    |
-| RoboSpatial-Home    | https://arxiv.org/abs/2411.16537   |https://huggingface.co/datasets/chanhee-luke/RoboSpatial-Home   |
-| EmbspatialBench    | https://arxiv.org/abs/2406.05756   | https://huggingface.co/datasets/Phineas476/EmbSpatial-Bench   |
-| All-Angles Bench    | https://arxiv.org/abs/2504.15280   | -   |
-| VSI-Bench    | https://arxiv.org/abs/2412.14171  | https://huggingface.co/datasets/nyu-visionx/VSI-Bench    |
-| SAT    | https://arxiv.org/abs/2412.07755   | https://huggingface.co/datasets/FlagEval/SAT   |
-| EgoPlan-Bench2    | https://arxiv.org/abs/2412.04447    | -    |
-| ERQA   | https://arxiv.org/abs/2503.20020    |https://huggingface.co/datasets/FlagEval/ERQA/    |
+- [Where2Place](https://huggingface.co/datasets/FlagEval/Where2Place)：[RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics](https://arxiv.org/abs/2406.10721)
+- [Blink](https://huggingface.co/datasets/BLINK-Benchmark/BLINK)：[BLINK: Multimodal Large Language Models Can See but Not Perceive](https://arxiv.org/abs/2404.12390)
+- [CVBench](https://huggingface.co/datasets/nyu-visionx/CV-Bench)：[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://arxiv.org/abs/2406.16860)
+- [RoboSpatial-Home](https://huggingface.co/datasets/chanhee-luke/RoboSpatial-Home)：[RoboSpatial: Teaching Spatial Understanding to 2D and 3D Vision-Language Models for Robotics](https://arxiv.org/abs/2411.16537)
+- [EmbspatialBench](https://huggingface.co/datasets/Phineas476/EmbSpatial-Bench)：[EmbSpatial-Bench: Benchmarking Spatial Understanding for Embodied Tasks with Large Vision-Language Models](https://arxiv.org/abs/2406.05756)
+- All-Angles Bench：[Seeing from Another Perspective: Evaluating Multi-View Understanding in MLLMs](https://arxiv.org/abs/2504.15280)
+- [VSI-Bench](https://huggingface.co/datasets/nyu-visionx/VSI-Bench)：[Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces](https://arxiv.org/abs/2412.14171)
+- [SAT](https://huggingface.co/datasets/FlagEval/SAT)：[SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models](https://arxiv.org/abs/2412.07755)
+- EgoPlan-Bench2：[EgoPlan-Bench2: A Benchmark for Multimodal Large Language Model Planning in Real-World Scenarios](https://arxiv.org/abs/2412.04447)
+- [ERQA](https://huggingface.co/datasets/FlagEval/ERQA)：[Gemini Robotics: Bringing AI into the Physical World](https://arxiv.org/abs/2503.20020)
 
 EmbodiedVerse-Open是一个由10个数据集构成的用于全面评测模型在具身智能场景下的meta dataset，包括：