Code for our paper "Sematic Representation for Dialogue Modeling" in ACL2021

Overview

AMR-Dialogue

An implementation for paper "Semantic Representation for Dialogue Modeling". You may find our paper here.

Requirements

  • python 3.6
  • pytorch 1.6
  • Tesla V100 (32G)
  • Memory > 150G

We recommend to use conda to manage virtual environments:

conda create --name <env> --file requirements.txt

Data

We provide preprocessed data for two tasks here [tobeadded].

Preprocessing

bash /path/to/code/preprocess.sh

Training

bash /path/to/code/run-dual(hier).sh

Evaluation

bash /path/to/code/eval.sh                   # for dialogue relation extraction
bash /path/to/code/decode.sh                 # for dialogue response generation

Todo

  • upload preprocessed data
  • upload trained checkpoint
  • clean code

References

@inproceedings{bai-etal-2020-online,
    title = "Semantic Representation for Dialogue Modeling",
    author = "Bai, Xuefeng  and 
      Chen, Yulong and
      Song, Linfeng  and
      Zhang, Yue",
    booktitle = "Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)",
    month = August,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "todo",
    doi = "todo",
    pages = "todo",
}
Owner
xfbai
Stay Hungry,Stay Foolish
xfbai
LBK 35 Dec 26, 2022
We are More than Our JOints: Predicting How 3D Bodies Move

We are More than Our JOints: Predicting How 3D Bodies Move Citation This repo contains the official implementation of our paper MOJO: @inproceedings{Z

72 Oct 20, 2022
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression YOLOv5 with alpha-IoU losses implemented in PyTorch. Example r

Jacobi(Jiabo He) 147 Dec 05, 2022
An End-to-End Machine Learning Library to Optimize AUC (AUROC, AUPRC).

Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a

Optimization for AI 176 Jan 07, 2023
Pytorch Lightning 1.2k Jan 06, 2023
Scaling and Benchmarking Self-Supervised Visual Representation Learning

FAIR Self-Supervision Benchmark is deprecated. Please see VISSL, a ground-up rewrite of benchmark in PyTorch. FAIR Self-Supervision Benchmark This cod

Meta Research 584 Dec 31, 2022
Official implementation of the paper Visual Parser: Representing Part-whole Hierarchies with Transformers

Visual Parser (ViP) This is the official implementation of the paper Visual Parser: Representing Part-whole Hierarchies with Transformers. Key Feature

Shuyang Sun 117 Dec 11, 2022
The implementation code for "DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction"

DAGAN This is the official implementation code for DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruct

TensorLayer Community 159 Nov 22, 2022
Arxiv harvester - Poor man's simple harvester for arXiv resources

Poor man's simple harvester for arXiv resources This modest Python script takes

Patrice Lopez 5 Oct 18, 2022
A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering.

DeepFilterNet A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering. libDF contains Rust code used for dat

Hendrik Schröter 292 Dec 25, 2022
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of

DeepHyper Team 214 Jan 08, 2023
Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging, ICCV2021 [PyTorch Code]

Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging, ICCV2021 [PyTorch Code]

Jian Zhang 20 Oct 24, 2022
Object detection and instance segmentation toolkit based on PaddlePaddle.

Object detection and instance segmentation toolkit based on PaddlePaddle.

9.3k Jan 02, 2023
PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

Keon Lee 67 Nov 14, 2022
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.

PySlowFast PySlowFast is an open source video understanding codebase from FAIR that provides state-of-the-art video classification models with efficie

Meta Research 5.3k Jan 03, 2023
Deep-learning-roadmap - All You Need to Know About Deep Learning - A kick-starter

Deep Learning - All You Need to Know Sponsorship To support maintaining and upgrading this project, please kindly consider Sponsoring the project deve

Instill AI 4.4k Dec 26, 2022
Pytorch implementation of NEGEV method. Paper: "Negative Evidence Matters in Interpretable Histology Image Classification".

Pytorch 1.10.0 code for: Negative Evidence Matters in Interpretable Histology Image Classification (https://arxiv. org/abs/xxxx.xxxxx) Citation: @arti

Soufiane Belharbi 4 Dec 01, 2022
PlenOctree Extraction algorithm

PlenOctrees_NeRF-SH This is an implementation of the Paper PlenOctrees for Real-time Rendering of Neural Radiance Fields. Not only the code provides t

49 Nov 05, 2022
naked is a Python tool which allows you to strip a model and only keep what matters for making predictions.

naked is a Python tool which allows you to strip a model and only keep what matters for making predictions. The result is a pure Python function with no third-party dependencies that you can simply c

Max Halford 24 Dec 20, 2022
Semi-automated OpenVINO benchmark_app with variable parameters

Semi-automated OpenVINO benchmark_app with variable parameters. User can specify multiple options for any parameters in the benchmark_app and the progam runs the benchmark with all combinations of gi

Yasunori Shimura 8 Apr 11, 2022