DEEPAGÉ: Answering Questions in Portuguese about the Brazilian Environment

Related tags

Deep Learningdeepage
Overview

DEEPAGÉ: Answering Questions in Portuguese about the Brazilian Environment

This repository is related to the paper DEEPAGÉ: Answering Questions in Portuguese about the Brazilian Environment, by Flávio Nakasato Cação1, Marcos Menon José1, André Seidel Oliveira1, Stefano Spindola1, Anna Helena Reali Costa1 and Fábio Gagliardi Cozman1. It was accepted at the Main Track of the 10th Brazilian Conference on Intelligent System (BRACIS'21).

Abstract: The challenge of climate change and biome conservation is one of the most pressing issues of our time - particularly in Brazil, where key environmental reserves are located. Given the availability of large textual databases on ecological themes, it is natural to resort to question answering (QA) systems to increase social awareness and understanding about these topics. In this work, we introduce multiple QA systems that combine in novel ways the BM25 algorithm, a sparse retrieval technique, with PTT5, a pre-trained state-of-the-art language model. Our QA systems focus on the Portuguese language, thus offering resources not found elsewhere in the literature. As training data, we collected questions from open-domain datasets, as well as content from the Portuguese Wikipedia and news from the press. We thus contribute with innovative architectures and novel applications, attaining an F1-score of 36.2 with our best model.

Acknowledgments

This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Finance Code 001) and by the Itaú Unibanco S.A., through the Programa de Bolsas Itaú (PBI) of the Centro de Ciência de Dados (C 2 D) of Escola Politécnica of Universidade de São Paulo (USP). We also gratefully acknowledge support from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (grants 312180/2018-7 and 310085/2020-9) and the Center for Artificial Intelligence (C4AI-USP), with support by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, grant 2019/ 07665-4) and by the IBM Corporation.



1 Polytechnic School, University of Sao Paulo, Sao Paulo, Brazil

YOLOPのPythonでのONNX推論サンプル

YOLOP-ONNX-Video-Inference-Sample YOLOPのPythonでのONNX推論サンプルです。 ONNXモデルは、hustvl/YOLOP/weights を使用しています。 Requirement OpenCV 3.4.2 or later onnxruntime 1.

KazuhitoTakahashi 8 Sep 05, 2022
Rotation-Only Bundle Adjustment

ROBA: Rotation-Only Bundle Adjustment Paper, Video, Poster, Presentation, Supplementary Material In this repository, we provide the implementation of

Seong 51 Nov 29, 2022
A basic duplicate image detection service using perceptual image hash functions and nearest neighbor search, implemented using faiss, fastapi, and imagehash

Duplicate Image Detection Getting Started Install dependencies pip install -r requirements.txt Run service python main.py Testing Test with pytest How

Matthew Podolak 21 Nov 11, 2022
Zero-shot Synthesis with Group-Supervised Learning (ICLR 2021 paper)

GSL - Zero-shot Synthesis with Group-Supervised Learning Figure: Zero-shot synthesis performance of our method with different dataset (iLab-20M, RaFD,

Andy_Ge 62 Dec 21, 2022
EMNLP 2021: Single-dataset Experts for Multi-dataset Question-Answering

MADE (Multi-Adapter Dataset Experts) This repository contains the implementation of MADE (Multi-adapter dataset experts), which is described in the pa

Princeton Natural Language Processing 68 Jul 18, 2022
PixelPyramids: Exact Inference Models from Lossless Image Pyramids (ICCV 2021)

PixelPyramids: Exact Inference Models from Lossless Image Pyramids This repository contains the PyTorch implementation of the paper PixelPyramids: Exa

Visual Inference Lab @TU Darmstadt 8 Dec 11, 2022
Watch faces morph into each other with StyleGAN 2, StyleGAN, and DCGAN!

FaceMorpher FaceMorpher is an innovative project to get a unique face morph (or interpolation for geeks) on a website. Yes, this means you can see fac

Anish 9 Jun 24, 2022
Byzantine-robust decentralized learning via self-centered clipping

Byzantine-robust decentralized learning via self-centered clipping In this paper, we study the challenging task of Byzantine-robust decentralized trai

EPFL Machine Learning and Optimization Laboratory 4 Aug 27, 2022
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)

Deep Daze mist over green hills shattered plates on the grass cosmic love and attention a time traveler in the crowd life during the plague meditative

Phil Wang 4.4k Jan 03, 2023
A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners

Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati

Aritra Roy Gosthipaty 59 Dec 10, 2022
Sequence to Sequence Models with PyTorch

Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha

Sandeep Subramanian 708 Dec 19, 2022
AI assistant built in python.the features are it can display time,say weather,open-google,youtube,instagram.

AI assistant built in python.the features are it can display time,say weather,open-google,youtube,instagram.

AK-Shanmugananthan 1 Nov 29, 2021
Predict multi paths to a moving person depending on his trajectory history.

Multi-future Trajectory Prediction The project is about using the Multiverse model to make possible multible-future trajectory prediction for a seen p

Said Gamal 1 Jan 18, 2022
A deep learning framework for historical document image analysis

DIVA-DAF Description A deep learning framework for historical document image analysis. How to run Install dependencies # clone project git clone https

9 Aug 04, 2022
Tree LSTM implementation in PyTorch

Tree-Structured Long Short-Term Memory Networks This is a PyTorch implementation of Tree-LSTM as described in the paper Improved Semantic Representati

Riddhiman Dasgupta 529 Dec 10, 2022
CVPR2021 Workshop - HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization.

HDRUNet [Paper Link] HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization By Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao an

XyChen 105 Dec 20, 2022
DI-smartcross - Decision Intelligence Platform for Traffic Crossing Signal Control

DI-smartcross DI-smartcross - Decision Intelligence Platform for Traffic Crossin

OpenDILab 213 Jan 02, 2023
OpenMMLab Computer Vision Foundation

English | 简体中文 Introduction MMCV is a foundational library for computer vision research and supports many research projects as below: MMCV: OpenMMLab

OpenMMLab 4.6k Jan 09, 2023
Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow

xRBM Library Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow Installation Using pip: pip install xrbm Examples Tut

Omid Alemi 55 Dec 29, 2022
Keras-retinanet - Keras implementation of RetinaNet object detection.

Keras RetinaNet Keras implementation of RetinaNet object detection as described in Focal Loss for Dense Object Detection by Tsung-Yi Lin, Priya Goyal,

Fizyr 4.3k Jan 01, 2023