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
Tensorflow 2 implementation of the paper: Learning and Evaluating Representations for Deep One-class Classification published at ICLR 2021

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Hso-groupie - A pwnable challenge in Real World CTF 4th

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Pytorch implementation of MLP-Mixer with loading pre-trained models.

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Qiushi Yang 2 Sep 29, 2022
Tensorflow implementation of "Learning Deep Features for Discriminative Localization"

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Taeksoo Kim 363 Jun 29, 2022
Code and data to accompany the camera-ready version of "Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation" in EMNLP 2021

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Mozhdeh Gheini 16 Jul 16, 2022
On the Adversarial Robustness of Visual Transformer

On the Adversarial Robustness of Visual Transformer Code for our paper "On the Adversarial Robustness of Visual Transformers"

Rulin Shao 35 Dec 14, 2022
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Update 2019/06/24: A model trained on 10% of the Shepard-Metzler dataset has been added, the following notebook explains the main features of this mod

Jesper Wohlert 313 Dec 27, 2022
PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.

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Yoonki Jeong 129 Dec 22, 2022
Alphabetical Letter Recognition

DecisionTrees-Image-Classification Alphabetical Letter Recognition In these demo we are using "Decision Trees" Our database is composed by Learning Im

Mohammed Firass 4 Nov 30, 2021
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code

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Pop-Out Motion: 3D-Aware Image Deformation via Learning the Shape Laplacian (CVPR 2022)

Pop-Out Motion Pop-Out Motion: 3D-Aware Image Deformation via Learning the Shape Laplacian (CVPR 2022) Jihyun Lee*, Minhyuk Sung*, Hyunjin Kim, Tae-Ky

Jihyun Lee 88 Nov 22, 2022
HCQ: Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval

HCQ: Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval [toc] 1. Introduction This repository provides the code for our paper at

13 Dec 08, 2022
FairFuzz: AFL extension targeting rare branches

FairFuzz An AFL extension to increase code coverage by targeting rare branches. FairFuzz has a particular advantage on programs with highly nested str

Caroline Lemieux 222 Nov 16, 2022
Data augmentation for NLP, accepted at EMNLP 2021 Findings

AEDA: An Easier Data Augmentation Technique for Text Classification This is the code for the EMNLP 2021 paper AEDA: An Easier Data Augmentation Techni

Akbar Karimi 81 Dec 09, 2022
Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"

Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo

Jeya Maria Jose 615 Dec 25, 2022
Pytorch implementation of Zero-DCE++

Zero-DCE++ You can find more details here: https://li-chongyi.github.io/Proj_Zero-DCE++.html. You can find the details of our CVPR version: https://li

Chongyi Li 157 Dec 23, 2022
Official Pytorch implementation of Meta Internal Learning

Official Pytorch implementation of Meta Internal Learning

10 Aug 24, 2022
Atif Hassan 103 Dec 14, 2022
competitions-v2

Codabench (formerly Codalab Competitions v2) Installation $ cp .env_sample .env $ docker-compose up -d $ docker-compose exec django ./manage.py migrat

CodaLab 21 Dec 02, 2022