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Update dataset card for parquet release

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  1. README.md +3 -36
README.md CHANGED
@@ -15,46 +15,13 @@ tags:
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  license: other
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  size_categories:
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  - 1K<n<10K
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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- dataset_info:
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- features:
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- - name: index
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- dtype: int64
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- - name: real_image_path
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- dtype: string
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- - name: image
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- dtype: image
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- - name: question
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- dtype: string
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- - name: question_type
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- dtype: string
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- - name: answer
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- dtype: string
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- - name: answer_type
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- dtype: string
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- - name: category
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- dtype: string
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- - name: split
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- dtype: string
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- - name: origin_dataset
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- dtype: string
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- splits:
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- - name: train
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- num_bytes: 2041995103
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- num_examples: 8657
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- download_size: 1991106566
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- dataset_size: 2041995103
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  ---
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  # HVSBench
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  HVSBench is a benchmark for evaluating how well multimodal large language models align with human perceptual behavior. It covers human visual system tasks across prominence, subitizing, prioritizing, free-viewing, and searching.
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- This Hugging Face release packages the cleaned TSV provided with the repository. It contains 8,657 question-answer examples and 7,507 unique raw images. The corresponding paper describes the full HVSBench benchmark with 85,147 multimodal QA pairs across 13 question types and 5 fields.
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  Paper: **Do MLLMs Exhibit Human-like Perceptual Behaviors? HVSBench: A Benchmark for MLLM Alignment with Human Perceptual Behavior**
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@@ -64,11 +31,11 @@ Project page: https://jiaying.link/HVSBench/
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  ## Dataset Structure
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- The dataset is uploaded using the Hugging Face `imagefolder` convention. The raw image for each row is exposed as the `image` feature by the dataset viewer. The original relative image path is retained in `real_image_path`, and `HVSBench_meta_clean_with_image.tsv` includes an explicit `image` column pointing to the uploaded raw image file.
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  Columns:
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- - `image`: raw RGB image
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  - `index`: source row index
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  - `real_image_path`: original relative path under `raw_datasets`
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  - `question`: benchmark prompt
 
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  license: other
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  size_categories:
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  - 1K<n<10K
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # HVSBench
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  HVSBench is a benchmark for evaluating how well multimodal large language models align with human perceptual behavior. It covers human visual system tasks across prominence, subitizing, prioritizing, free-viewing, and searching.
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+ This Hugging Face release packages the cleaned subset provided with the repository as parquet shards with embedded image bytes. It contains 8,657 question-answer examples and 7,507 unique raw images referenced through the `image` column. The corresponding paper describes the full HVSBench benchmark with 85,147 multimodal QA pairs across 13 question types and 5 fields.
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  Paper: **Do MLLMs Exhibit Human-like Perceptual Behaviors? HVSBench: A Benchmark for MLLM Alignment with Human Perceptual Behavior**
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  ## Dataset Structure
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+ The dataset is uploaded as parquet shards. The `image` feature contains the image data embedded in parquet, and `real_image_path` preserves the original relative source path under `raw_datasets`.
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  Columns:
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+ - `image`: raw RGB image embedded in parquet
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  - `index`: source row index
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  - `real_image_path`: original relative path under `raw_datasets`
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  - `question`: benchmark prompt