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update README

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  1. lb_info.py +4 -3
lb_info.py CHANGED
@@ -25,8 +25,9 @@ CITATION_BUTTON_TEXT = r"""@misc{2023opencompass,
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  CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
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  # CONSTANTS-TEXT
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  LEADERBORAD_INTRODUCTION = """# OpenVLM Leaderboard
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- ### Welcome to the OpenVLM Leaderboard! On this leaderboard we share the evaluation results of VLMs obtained by the OpenSource Framework [**VLMEvalKit**](https://github.com/open-compass/VLMEvalKit) πŸ†
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- ### Currently, OpenVLM Leaderboard covers {} different VLMs (including GPT-4v, Gemini, QwenVLPlus, LLaVA, etc.) and {} different multi-modal benchmarks.
 
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  This leaderboard was last updated: {}.
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  """
@@ -131,7 +132,7 @@ LEADERBOARD_MD['COCO_VAL'] = """
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  """
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  LEADERBOARD_MD['ScienceQA_VAL'] = """
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- # ScienceQA Evaluation Results
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  - We benchmark the **image** subset of ScienceQA validation and test set, and report the Top-1 accuracy.
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  - During evaluation, we use `GPT-3.5-Turbo-0613` as the choice extractor for all VLMs if the choice can not be extracted via heuristic matching. **Zero-shot** inference is adopted.
 
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  CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
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  # CONSTANTS-TEXT
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  LEADERBORAD_INTRODUCTION = """# OpenVLM Leaderboard
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+ ## Welcome to the OpenVLM Leaderboard! On this leaderboard we share the evaluation results of VLMs obtained by the OpenSource Framework:
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+ ## [*VLMEvalKit*: A Toolkit for Evaluating Large Vision-Language Models](https://github.com/open-compass/VLMEvalKit) πŸ†
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+ ## Currently, OpenVLM Leaderboard covers {} different VLMs (including GPT-4v, Gemini, QwenVLPlus, LLaVA, etc.) and {} different multi-modal benchmarks.
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  This leaderboard was last updated: {}.
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  """
 
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  """
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  LEADERBOARD_MD['ScienceQA_VAL'] = """
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+ ## ScienceQA Evaluation Results
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  - We benchmark the **image** subset of ScienceQA validation and test set, and report the Top-1 accuracy.
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  - During evaluation, we use `GPT-3.5-Turbo-0613` as the choice extractor for all VLMs if the choice can not be extracted via heuristic matching. **Zero-shot** inference is adopted.