Feedback is important: response-aware feedback mechanism for background based conversation

Last update: Sep 29, 2022

Related tags

Deep Learning RFM

Overview

RFM

The code for the paper: "Feedback is important: response-aware feedback mechanism for background based conversation."

Requirements

python 3.7
pytorch 1.7.0

Datasets

Download the raw data version of Holl-E, and put the raw data files (train_data.json, dev_data.json and test_data.json）in the directory /dataset/raw_data.
Then, run the preprocessing script:

python Prepare_holl.py

Download the glove.6B.300d.txt and put it in /dataset/oracle and /dataset/mixed.

Run training, validation, and testing

To train or test your model, run:

python -m torch.distributed.launch --nproc_per_node=num_GPU Run_RFM.py --mode='train/test'

Addition

More descriptions will be released in a few days...

Owner

Jiatao Chen

GitHub Repository

Hierarchical Cross-modal Talking Face Generation with Dynamic Pixel-wise Loss （ATVGnet）

Hierarchical Cross-modal Talking Face Generation with Dynamic Pixel-wise Loss （ATVGnet） By Lele Chen , Ross K Maddox, Zhiyao Duan, Chenliang Xu. Unive

218 Dec 27, 2022

LBBA-boosted WSOD

LBBA-boosted WSOD Summary Our code is based on ruotianluo/pytorch-faster-rcnn and WSCDN Sincerely thanks for your resources. Newer version of our code

20 Sep 19, 2022

Colour detection is necessary to recognize objects, it is also used as a tool in various image editing and drawing apps.

Colour Detection On Image Colour detection is the process of detecting the name of any color. Simple isn’t it? Well, for humans this is an extremely e

1 Jan 13, 2022

Implementation of momentum^2 teacher

Momentum^2 Teacher: Momentum Teacher with Momentum Statistics for Self-Supervised Learning Requirements All experiments are done with python3.6, torch

121 Sep 26, 2022

Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab.

CLIP-Guided-Diffusion Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab. Original colab notebooks by Ka

336 Dec 09, 2022

An unofficial personal implementation of UM-Adapt, specifically to tackle joint estimation of panoptic segmentation and depth prediction for autonomous driving datasets.

Semisupervised Multitask Learning This repository is an unofficial and slightly modified implementation of UM-Adapt[1] using PyTorch. This code primar

11 Nov 25, 2022

Speech-Emotion-Analyzer - The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

Speech Emotion Analyzer The idea behind creating this project was to build a machine learning model that could detect emotions from the speech we have

965 Dec 24, 2022

DWIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data.

DWIPrep: A Robust Preprocessing Pipeline for dMRI Data DWIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data. The transp

1 Jan 09, 2023

Universal Adversarial Triggers for Attacking and Analyzing NLP (EMNLP 2019)

Universal Adversarial Triggers for Attacking and Analyzing NLP This is the official code for the EMNLP 2019 paper, Universal Adversarial Triggers for

248 Dec 17, 2022

This repository is a series of notebooks that show solutions for the projects at Dataquest.io.

Dataquest Project Solutions This repository is a series of notebooks that show solutions for the projects at Dataquest.io. Of course, there are always

1.1k Dec 30, 2022

Official repository for "PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation"

pair-emnlp2020 Official repository for the paper: Xinyu Hua and Lu Wang: PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long

31 Oct 13, 2022

Unofficial PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution

PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution [arXiv 2021].

122 Dec 12, 2022

CARL provides highly configurable contextual extensions to several well-known RL environments.

CARL (context adaptive RL) provides highly configurable contextual extensions to several well-known RL environments.

51 Dec 28, 2022

Code Repository for Liquid Time-Constant Networks (LTCs)

Liquid time-constant Networks (LTCs) [Update] A Pytorch version is added in our sister repository: https://github.com/mlech26l/keras-ncp This is the o

553 Dec 27, 2022

[ArXiv 2021] Data-Efficient Instance Generation from Instance Discrimination

InsGen - Data-Efficient Instance Generation from Instance Discrimination Data-Efficient Instance Generation from Instance Discrimination Ceyuan Yang,

93 Dec 25, 2022

This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning].

CG3 This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning]. R

12 Oct 28, 2022