Improve dataset card with metadata, description, and sample usage

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by nielsr HF Staff - opened
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  1. README.md +50 -3
README.md CHANGED
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- Link to the project: https://pageguide.github.io/
 
 
 
 
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- Link to the paper: https://huggingface.co/papers/2604.23772
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- Link to the code: https://github.com/tin-xai/pageguide
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ task_categories:
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+ - other
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+ license: mit
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+ ---
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+ # PageGuide Dataset
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+ This repository contains dataset artifacts from the paper [PageGuide: Browser extension to assist users in navigating a webpage and locating information](https://huggingface.co/papers/2604.23772).
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+
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+ * **Project Page:** https://pageguide.github.io/
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+ * **Repository:** https://github.com/tin-xai/pageguide
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+ * **Paper:** [Hugging Face Paper Page](https://huggingface.co/papers/2604.23772)
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+
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+ ---
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+
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+ ## Dataset Description
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+
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+ PageGuide was evaluated in a controlled within-subjects user study. The evaluation data is structured into four datasets:
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+
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+ ### 1. `pageguide_userstudy`
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+ * **Purpose:** Raw interaction logs from the user study — completion times, chat transcripts, correctness labels, paired statistical results, and post-study survey responses.
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+ * **Sample Usage:**
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+ ```python
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+ from datasets import load_dataset
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+ tasks = load_dataset("ttn0011/pageguide_userstudy", data_files="tasks.csv", split="train").to_pandas()
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+ paired = load_dataset("ttn0011/pageguide_userstudy", data_files="paired_times.csv", split="train").to_pandas()
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+ ```
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+
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+ ### 2. `pageguide_find_data`
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+ * **Purpose:** Task stimuli for the **Find** condition — 10 real webpages (NASA, Wikipedia, Cleveland Clinic, WWF, Britannica, JMLR) each annotated with up to 2 factual questions, ground-truth answers, and supporting evidence spans.
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+ * **Sample Usage:**
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+ ```python
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+ from datasets import load_dataset
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+ find_tasks = load_dataset("ttn0011/pageguide_find_data", split="train").to_pandas()
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+ ```
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+
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+ ### 3. `pageguide_guide_data`
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+ * **Purpose:** Task stimuli for the **Guide** condition — 7 procedural tasks across 6 platforms (Google Sheets, Google Docs, Google Slides, Coda, TradingView, Scratch), labelled Easy or Medium difficulty.
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+ * **Sample Usage:**
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+ ```python
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+ from datasets import load_dataset
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+ guide_tasks = load_dataset("ttn0011/pageguide_guide_data", split="train").to_pandas()
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+ ```
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+
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+ ### 4. `pageguide_hide_data`
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+ * **Purpose:** Task stimuli for the **Hide** condition — 37 annotated webpage snapshots (Amazon, Netflix, TechCrunch, Allrecipes, Spotify, Yelp, and more) with `(user_goal, hide_query, difficulty, hidden_elements)` annotations and ground-truth CSS selectors.
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+ * **Sample Usage:**
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+ ```python
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+ from datasets import load_dataset
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+ hide_tasks = load_dataset("ttn0011/pageguide_hide_data", split="train").to_pandas()
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+ ```