Release of the ConditionalQA dataset

Overview

ConditionalQA

Datasets accompanying the paper ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers.

Disclaimer

This dataset should ONLY be used for NLP research purpose. Answers are NOT verified by legal professionals and should NOT be used for any legal purposes.

Evaluate

Please generate your predictions using the format sample_output.json. Run the following command to evaluate your predictions with evaluate.py:

python evaluate.py --pred_file=sample_output.json --ref_file=v1_0/dev.json

Leaderboard

Submit your predictions to the Leaderboard.

Please email your Codalab username to [email protected] if you would like your results to be added to the leaderboard. Include your organisation, a link to your paper, and a short description of your model in the email.

Citation

If you use these datasets please cite the following:

TBD
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AImageLab 277 Dec 28, 2022
A small tool to joint picture including gif

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3 Dec 15, 2021
Deep Learning Theory

Deep Learning Theory 整理了一些深度学习的理论相关内容,持续更新。 Overview Recent advances in deep learning theory 总结了目前深度学习理论研究的六个方向的一些结果,概述型,没做深入探讨(2021)。 1.1 complexity

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BankNote-Net: Open dataset and encoder model for assistive currency recognition

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Focal Loss for Dense Rotation Object Detection

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17 Nov 24, 2021
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2 Jul 01, 2022
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DirectCLR DirectCLR is a simple contrastive learning model for visual representation learning. It does not require a trainable projector as SimCLR. It

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[ICCV21] Self-Calibrating Neural Radiance Fields

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381 Dec 30, 2022