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

Related tags

Deep LearningRFM
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
Jiatao Chen
GitHub Repository
《Image2Reverb: Cross-Modal Reverb Impulse Response Synthesis》(2021)

Image2Reverb Image2Reverb is an end-to-end neural network that generates plausible audio impulse responses from single images of acoustic environments

Nikhil Singh 48 Nov 27, 2022
Code to accompany the paper "Finding Bipartite Components in Hypergraphs", which is published in NeurIPS'21.

Finding Bipartite Components in Hypergraphs This repository contains code to accompany the paper "Finding Bipartite Components in Hypergraphs", publis

Peter Macgregor 5 May 06, 2022
Model-based reinforcement learning in TensorFlow

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

46 Nov 09, 2022
An intelligent, flexible grammar of machine learning.

An english representation of machine learning. Modify what you want, let us handle the rest. Overview Nylon is a python library that lets you customiz

Palash Shah 79 Dec 02, 2022
All public open-source implementations of convnets benchmarks

convnet-benchmarks Easy benchmarking of all public open-source implementations of convnets. A summary is provided in the section below. Machine: 6-cor

Soumith Chintala 2.7k Dec 30, 2022
Robust Partial Matching for Person Search in the Wild

APNet for Person Search Introduction This is the code of Robust Partial Matching for Person Search in the Wild accepted in CVPR2020. The Align-to-Part

Yingji Zhong 36 Dec 18, 2022
DEMix Layers for Modular Language Modeling

DEMix This repository contains modeling utilities for "DEMix Layers: Disentangling Domains for Modular Language Modeling" (Gururangan et. al, 2021). T

Suchin 43 Nov 11, 2022
Bayesian algorithm execution (BAX)

Bayesian Algorithm Execution (BAX) Code for the paper: Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mut

Willie Neiswanger 38 Dec 08, 2022
Official Repository of NeurIPS2021 paper: PTR

PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning Figure 1. Dataset Overview. Introduction A critical aspect of human vis

Yining Hong 32 Jun 02, 2022
GPU-accelerated Image Processing library using OpenCL

pyclesperanto pyclesperanto is a python package for clEsperanto - a multi-language framework for GPU-accelerated image processing. clEsperanto uses Op

17 Dec 25, 2022
This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug

Yue Yu 58 Dec 21, 2022
TensorFlow code for the neural network presented in the paper: "Structural Language Models of Code" (ICML'2020)

SLM: Structural Language Models of Code This is an official implementation of the model described in: "Structural Language Models of Code" [PDF] To ap

73 Nov 06, 2022
Using machine learning to predict and analyze high and low reader engagement for New York Times articles posted to Facebook.

How The New York Times can increase Engagement on Facebook Using machine learning to understand characteristics of news content that garners "high" Fa

Jessica Miles 0 Sep 16, 2021
Memory efficient transducer loss computation

Introduction This project implements the optimization techniques proposed in Improving RNN Transducer Modeling for End-to-End Speech Recognition to re

Fangjun Kuang 51 Nov 25, 2022
Code to reproduce the experiments in the paper "Transformer Based Multi-Source Domain Adaptation" (EMNLP 2020)

Transformer Based Multi-Source Domain Adaptation Dustin Wright and Isabelle Augenstein To appear in EMNLP 2020. Read the preprint: https://arxiv.org/a

CopeNLU 36 Dec 05, 2022
Embracing Single Stride 3D Object Detector with Sparse Transformer

SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer

TuSimple 385 Dec 28, 2022
A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

SVHNClassifier-PyTorch A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks If

Potter Hsu 182 Jan 03, 2023
Fast convergence of detr with spatially modulated co-attention

Fast convergence of detr with spatially modulated co-attention Usage There are no extra compiled components in SMCA DETR and package dependencies are

peng gao 135 Dec 07, 2022
Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder

Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder Authors: - Eashan Adhikarla - Dan Luo - Dr. Brian D. Davison Abstract Many

Eashan Adhikarla 4 Dec 25, 2022
PyTorch implementation of Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network

hierarchical-multi-label-text-classification-pytorch Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach This

Mingu Kang 17 Dec 13, 2022