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@@ -9,11 +9,19 @@ language:
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  tags:
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  - Long Context
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  - reasoning
 
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  size_categories:
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  - n<1K
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  license: apache-2.0
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  ---
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  # LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks
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  🌐 Project Page: https://longbench2.github.io
@@ -28,45 +36,6 @@ To elaborate, LongBench v2 consists of 503 challenging multiple-choice questions
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  **🔍 With LongBench v2, we are eager to find out how scaling inference-time compute will affect deep understanding and reasoning in long-context scenarios. View our 🏆 leaderboard [here](https://longbench2.github.io/#leaderboard) (updating).**
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- # 🔨 How to use it?
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-
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- #### Loading Data
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-
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- You can download and load the **LongBench v2** data through the Hugging Face datasets ([🤗 HF Repo](https://huggingface.co/datasets/THUDM/LongBench-v2)):
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- ```python
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- from datasets import load_dataset
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- dataset = load_dataset('THUDM/LongBench-v2', split='train')
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- ```
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- Alternatively, you can download the file from [this link](https://huggingface.co/datasets/THUDM/LongBench-v2/resolve/main/data.json) to load the data.
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-
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- #### Data Format
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-
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- All data in **LongBench v2** are standardized to the following format:
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-
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- ```json
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- {
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- "_id": "Unique identifier for each piece of data",
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- "domain": "The primary domain category of the data",
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- "sub_domain": "The specific sub-domain category within the domain",
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- "difficulty": "The difficulty level of the task, either 'easy' or 'hard'",
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- "length": "The length category of the task, which can be 'short', 'medium', or 'long'",
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- "question": "The input/command for the task, usually short, such as questions in QA, queries in many-shot learning, etc",
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- "choice_A": "Option A", "choice_B": "Option B", "choice_C": "Option C", "choice_D": "Option D",
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- "answer": "The groundtruth answer, denoted as A, B, C, or D",
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- "context": "The long context required for the task, such as documents, books, code repositories, etc."
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- }
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- ```
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-
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- #### Evaluation
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-
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- This repository provides data download for LongBench v2. If you wish to use this dataset for automated evaluation, please refer to our [github](https://github.com/THUDM/LongBench).
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-
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- # Dataset Statistics
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-
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- <p align="left"><img width="60%" alt="data_instance" src="https://cdn-uploads.huggingface.co/production/uploads/64ed568ccf6118a9379a61b8/6i10a4KKy5WS2xGAQ8h9E.png"></p>
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-
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- <p align="left"><img width="70%" alt="data_instance" src="https://cdn-uploads.huggingface.co/production/uploads/64ed568ccf6118a9379a61b8/qWMf-xKmX17terdKxu9oa.png"></p>
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-
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  # Citation
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  ```
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  @article{bai2024longbench2,
 
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  tags:
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  - Long Context
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  - reasoning
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+ - llama.cpp
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  size_categories:
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  - n<1K
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  license: apache-2.0
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  ---
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+ LongBench v2 converted for the llama.cpp perplexity multiple chice tool.
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+
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+ > [!WARNING]
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+ > !! Currently does not work, will fix it in the near future. Probably.
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+
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+ ---
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+
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  # LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks
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  🌐 Project Page: https://longbench2.github.io
 
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  **🔍 With LongBench v2, we are eager to find out how scaling inference-time compute will affect deep understanding and reasoning in long-context scenarios. View our 🏆 leaderboard [here](https://longbench2.github.io/#leaderboard) (updating).**
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  # Citation
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  ```
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  @article{bai2024longbench2,