The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization

Related tags

Deep LearningPRIMER
Overview

PRIMER

The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization.

PRIMER is a pre-trained model for multi-document representation with focus on summarization that reduces the need for dataset-specific architectures and large amounts of fine-tuning labeled data. With extensive experiments on 6 multi-document summarization datasets from 3 different domains on the zero-shot, few-shot and full-supervised settings, PRIMER outperforms current state-of-the-art models on most of these settings with large margins.

Set up

  1. Create new virtual environment by
conda create --name primer python=3.7
conda activate primer
conda install cudatoolkit=10.0
  1. Install Longformer by
pip install git+https://github.com/allenai/longformer.git
  1. Install requirements to run the summarization scripts and data generation scripts by
pip install -r requirements.txt

Usage of PRIMER

  1. Download the pre-trained PRIMER model here to ./PRIMER_model
  2. Load the tokenizer and model by
from transformers import AutoTokenizer
from longformer import LongformerEncoderDecoderForConditionalGeneration
from longformer import LongformerEncoderDecoderConfig

tokenizer = AutoTokenizer.from_pretrained('./PRIMER_model/')
config = LongformerEncoderDecoderConfig.from_pretrained('./PRIMER_model/')
model = LongformerEncoderDecoderForConditionalGeneration.from_pretrained(
            './PRIMER_model/', config=config)

Make sure the documents separated with <doc-sep> in the input.

Summarization Scripts

You can use script/primer_main.py for pre-train/train/test PRIMER, and script/compared_model_main.py for train/test BART/PEGASUS/LED.

Pre-training Data Generation

Newshead: we crawled the newshead dataset using the original code, and cleaned up the crawled data, the final newshead dataset can be found here.

You can use utils/pretrain_preprocess.py to generate pre-training data.

  1. Generate data with scores and entities with --mode compute_all_scores
  2. Generate pre-training data with --mode pretraining_data_with_score:
    • Pegasus: --strategy greedy --metric pegasus_score
    • Entity_Pyramid: --strategy greedy_entity_pyramid --metric pyramid_rouge

Datasets

  • For Multi-News and Multi-XScience, it will automatically download from Huggingface.
  • WCEP-10: the preprocessed version can be found here
  • Wikisum: we only use a small subset for few-shot training(10/100) and testing(3200). The subset we used can be found here. Note we have significantly more examples than we used in train.pt and valid.pt, as we sample 10/100 examples multiple times in the few-shot setting, and we need to make sure it has a large pool to sample from.
  • DUC2003/2004: You need to apply for access based on the instruction
  • arXiv: you can find the data we used in this repo
Pytorch implementation of Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization https://arxiv.org/abs/2008.11646

[TCSVT] Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization LPN [Paper] NEWs Prerequisites Python 3.6 GPU Memory = 8G Numpy 1.

46 Dec 14, 2022
Barlow Twins and HSIC

Barlow Twins and HSIC Unofficial Pytorch implementation for Barlow Twins and HSIC_SSL on small datasets (CIFAR10, STL10, and Tiny ImageNet). Correspon

Yao-Hung Hubert Tsai 49 Nov 24, 2022
Perfect implement. Model shared. x0.5 (Top1:60.646) and 1.0x (Top1:69.402).

Shufflenet-v2-Pytorch Introduction This is a Pytorch implementation of faceplusplus's ShuffleNet-v2. For details, please read the following papers:

423 Dec 07, 2022
Course materials for Fall 2021 "CIS6930 Topics in Computing for Data Science" at New College of Florida

Fall 2021 CIS6930 Topics in Computing for Data Science This repository hosts course materials used for a 13-week course "CIS6930 Topics in Computing f

Yoshi Suhara 101 Nov 30, 2022
FAVD: Featherweight Assisted Vulnerability Discovery

FAVD: Featherweight Assisted Vulnerability Discovery This repository contains the replication package for the paper "Featherweight Assisted Vulnerabil

secureIT 4 Sep 16, 2022
Continuous Security Group Rule Change Detection & Response at scale

Introduction Get notified of Security Group Changes across all AWS Accounts & Regions in an AWS Organization, with the ability to respond/revert those

Raajhesh Kannaa Chidambaram 3 Aug 13, 2022
GAN-based 3D human pose estimation model for 3DV'17 paper

Tensorflow implementation for 3DV 2017 conference paper "Adversarially Parameterized Optimization for 3D Human Pose Estimation". @inproceedings{jack20

Dominic Jack 15 Feb 27, 2021
Face recognize system

FRS Face_recognize_system This project contains my work that target on solving some problems of FRS: Face detection: Retinaface Face anti-spoofing: Fo

Tran Anh Tuan 4 Nov 18, 2021
gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks.

gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks. It is built on top of the OpenAI G

Robin Henry 99 Dec 12, 2022
Source code of SIGIR2021 Paper 'One Chatbot Per Person: Creating Personalized Chatbots based on Implicit Profiles'

DHAP Source code of SIGIR2021 Long Paper: One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles . Preinstallation Fir

ZYMa 32 Dec 06, 2022
Code for "Modeling Indirect Illumination for Inverse Rendering", CVPR 2022

Modeling Indirect Illumination for Inverse Rendering Project Page | Paper | Data Preparation Set up the python environment conda create -n invrender p

ZJU3DV 116 Jan 03, 2023
The world's simplest facial recognition api for Python and the command line

Face Recognition You can also read a translated version of this file in Chinese 简体中文版 or in Korean 한국어 or in Japanese 日本語. Recognize and manipulate fa

Adam Geitgey 46.9k Jan 03, 2023
Research code of ICCV 2021 paper "Mesh Graphormer"

MeshGraphormer ✨ ✨ This is our research code of Mesh Graphormer. Mesh Graphormer is a new transformer-based method for human pose and mesh reconsructi

Microsoft 251 Jan 08, 2023
[ICME 2021 Oral] CORE-Text: Improving Scene Text Detection with Contrastive Relational Reasoning

CORE-Text: Improving Scene Text Detection with Contrastive Relational Reasoning This repository is the official PyTorch implementation of CORE-Text, a

Jingyang Lin 18 Aug 11, 2022
Reproducible research and reusable acyclic workflows in Python. Execute code on HPC systems as if you executed them on your personal computer!

Reproducible research and reusable acyclic workflows in Python. Execute code on HPC systems as if you executed them on your machine! Motivation Would

Joeri Hermans 15 Sep 11, 2022
[ICCV21] Code for RetrievalFuse: Neural 3D Scene Reconstruction with a Database

RetrievalFuse Paper | Project Page | Video RetrievalFuse: Neural 3D Scene Reconstruction with a Database Yawar Siddiqui, Justus Thies, Fangchang Ma, Q

Yawar Nihal Siddiqui 75 Dec 22, 2022
Python Tensorflow 2 scripts for detecting objects of any class in an image without knowing their label.

Tensorflow-Mobile-Generic-Object-Localizer Python Tensorflow 2 scripts for detecting objects of any class in an image without knowing their label. Ori

Ibai Gorordo 11 Nov 15, 2022
2021:"Bridging Global Context Interactions for High-Fidelity Image Completion"

TFill arXiv | Project This repository implements the training, testing and editing tools for "Bridging Global Context Interactions for High-Fidelity I

Chuanxia Zheng 111 Jan 08, 2023
This is an example of object detection on Micro bacterium tuberculosis using Mask-RCNN

Mask-RCNN on Mycobacterium tuberculosis This is an example of object detection on Mycobacterium Tuberculosis using Mask RCNN. Implement of Mask R-CNN

Jun-En Ding 1 Sep 16, 2021
Stroke-predictions-ml-model - Machine learning model to predict individuals chances of having a stroke

stroke-predictions-ml-model machine learning model to predict individuals chance

Alex Volchek 1 Jan 03, 2022