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
Official implementation of "A Unified Objective for Novel Class Discovery", ICCV2021 (Oral)

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Supplemental learning materials for "Fourier Feature Networks and Neural Volume Rendering"

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Matthew A Johnson 133 Dec 26, 2022
Implementation of Pix2Seq in PyTorch

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Tony Shin 9 Dec 15, 2022
An original implementation of "MetaICL Learning to Learn In Context" by Sewon Min, Mike Lewis, Luke Zettlemoyer and Hannaneh Hajishirzi

MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu

Meta Research 141 Jan 07, 2023
Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021

LoFTR: Detector-Free Local Feature Matching with Transformers Project Page | Paper LoFTR: Detector-Free Local Feature Matching with Transformers Jiami

ZJU3DV 1.4k Jan 04, 2023
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)

PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J

AI Wizards for Software Management (AWSM) Research Group 14 Nov 13, 2022
“Data Augmentation for Cross-Domain Named Entity Recognition” (EMNLP 2021)

Data Augmentation for Cross-Domain Named Entity Recognition Authors: Shuguang Chen, Gustavo Aguilar, Leonardo Neves and Thamar Solorio This repository

<a href=[email protected]"> 18 Sep 10, 2022
A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)

Graph Wavelet Neural Network ⠀⠀ A PyTorch implementation of Graph Wavelet Neural Network (ICLR 2019). Abstract We present graph wavelet neural network

Benedek Rozemberczki 490 Dec 16, 2022
The PyTorch implementation for paper "Neural Texture Extraction and Distribution for Controllable Person Image Synthesis" (CVPR2022 Oral)

ArXiv | Get Start Neural-Texture-Extraction-Distribution The PyTorch implementation for our paper "Neural Texture Extraction and Distribution for Cont

Ren Yurui 111 Dec 10, 2022
chen2020iros: Learning an Overlap-based Observation Model for 3D LiDAR Localization.

Overlap-based 3D LiDAR Monte Carlo Localization This repo contains the code for our IROS2020 paper: Learning an Overlap-based Observation Model for 3D

Photogrammetry & Robotics Bonn 219 Dec 15, 2022
(CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds by Mutian Xu*, Runyu Ding*, Hengshuang Zhao, and Xiaojuan Qi. Int

CVMI Lab 228 Dec 25, 2022
Robotics environments

Robotics environments Details and documentation on these robotics environments are available in OpenAI's blog post and the accompanying technical repo

Farama Foundation 121 Dec 28, 2022
An implementation of the 1. Parallel, 2. Streaming, 3. Randomized SVD using MPI4Py

PYPARSVD This implementation allows for a singular value decomposition which is: Distributed using MPI4Py Streaming - data can be shown in batches to

Romit Maulik 44 Dec 31, 2022
mlpack: a scalable C++ machine learning library --

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

mlpack 4.2k Jan 09, 2023
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing da

MIT CSAIL Computer Vision 4.5k Jan 08, 2023
Source code for Transformer-based Multi-task Learning for Disaster Tweet Categorisation (UCD's participation in TREC-IS 2020A, 2020B and 2021A).

Source code for "UCD participation in TREC-IS 2020A, 2020B and 2021A". *** update at: 2021/05/25 This repo so far relates to the following work: Trans

Congcong Wang 4 Oct 19, 2021
Finetuning Pipeline

KLUE Baseline Korean(한국어) KLUE-baseline contains the baseline code for the Korean Language Understanding Evaluation (KLUE) benchmark. See our paper fo

74 Dec 13, 2022
Official implementation for Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting

1 SNAS4MTF This repo is the official implementation for Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting. 1.1 The frame

SZJ 5 Sep 21, 2022
Relative Positional Encoding for Transformers with Linear Complexity

Stochastic Positional Encoding (SPE) This is the source code repository for the ICML 2021 paper Relative Positional Encoding for Transformers with Lin

Antoine Liutkus 48 Nov 16, 2022
Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.

Non-Metric Space Library (NMSLIB) Important Notes NMSLIB is generic but fast, see the results of ANN benchmarks. A standalone implementation of our fa

2.9k Jan 04, 2023