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Add task category and link to paper (#1)

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- Add task category and link to paper (0869aaf7acaade9ec4fefa0ffd49cbc52ae72e22)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

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  1. README.md +10 -9
README.md CHANGED
@@ -1,16 +1,20 @@
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  ---
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  license: apache-2.0
 
 
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  tags:
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- - multimodal
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- - ophthalmology
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- - OCT
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- - benchmark
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- - medical
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- - visual question answering
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  ---
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  # πŸ€— OCT-Bench
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  ![Overview](overview.png)
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  We introduce OCT-Bench, a comprehensive benchmark for evaluating Multimodal Large Language Models (MLLMs) on optical coherence tomography (OCT) image understanding. OCT-Bench comprises 10,076 expert-verified multiple-choice questions from 4,137 OCT images across seven public datasets and evaluates 3 capability dimensions, 9 capability groups, and 20 fine-grained tasks covering perception, cognition, and clinical reasoning. We benchmark 20 representative MLLMs, including proprietary, open-source, and medical-domain models, providing a comprehensive assessment of OCT understanding capabilities.
@@ -19,7 +23,6 @@ For detailed usage and instructions, please refer to the [GitHub page](https://g
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  You can download **OCT-Bench**. The expected directory structure is:
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-
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  ```
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  OCT-Bench
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  β”œβ”€β”€ images
@@ -30,6 +33,4 @@ OCT-Bench
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  β”œβ”€β”€ T01_VQA.jsonl
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  β”œβ”€β”€ T02_VQA.jsonl
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  └── ...
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-
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-
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  ```
 
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  ---
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  license: apache-2.0
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+ task_categories:
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+ - image-text-to-text
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  tags:
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+ - multimodal
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+ - ophthalmology
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+ - OCT
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+ - benchmark
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+ - medical
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+ - visual question answering
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  ---
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  # πŸ€— OCT-Bench
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+ [Paper](https://huggingface.co/papers/2607.16609) | [GitHub](https://github.com/baochenfu/OCT-Bench)
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+
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  ![Overview](overview.png)
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  We introduce OCT-Bench, a comprehensive benchmark for evaluating Multimodal Large Language Models (MLLMs) on optical coherence tomography (OCT) image understanding. OCT-Bench comprises 10,076 expert-verified multiple-choice questions from 4,137 OCT images across seven public datasets and evaluates 3 capability dimensions, 9 capability groups, and 20 fine-grained tasks covering perception, cognition, and clinical reasoning. We benchmark 20 representative MLLMs, including proprietary, open-source, and medical-domain models, providing a comprehensive assessment of OCT understanding capabilities.
 
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  You can download **OCT-Bench**. The expected directory structure is:
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  ```
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  OCT-Bench
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  β”œβ”€β”€ images
 
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  β”œβ”€β”€ T01_VQA.jsonl
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  β”œβ”€β”€ T02_VQA.jsonl
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  └── ...
 
 
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  ```