This repository accompanies the ACM TOIS paper "What can I cook with these ingredients?" - Understanding cooking-related information needs in conversational search

Overview

beersoup In this repository you find data that has been gathered when conducting in-situ experiments in a conversational cooking setting. These data include transcripts,annotations and code to analyse these data.

When you are here while reading our paper, you might have following questions:

Where can I find the transcripts?

The raw transcripts are located in the transcripts folder. All experiments were conducted in Germany. Therefore, we provide the original german version as well as an english version transcribed with DeepL. Since we put much more effort in the transcription and annotation process compared to our workshop paper (=pilot study), we also provide the annotated data from that paper (see folder transcripts/workshop_paper).

Where is the information need taxonomy?

A visual representation can be found in the annotation folder. InformationNeedTaxonomy.svg is the file you are looking for.

Where is the codebook?

A description of all information needs as well as examples for them are located in the annotation folder. annotation_schema_cookversational_search_german.xlsx is the german version, annotation_schema_cookversational_search.xlsx is the english one. The codebook from our pilot study is located in this folder, too.

Where is the code for the machine learning experiments?

You find code for both the baseline models, the BERT based models and the results in the experiments folder.

Is there a notebook that contains the statistical analyses?

Yes! Statistical Analysis.ipynb in the experimentsfolder is the relevant file.

Where is the CookversationalSearch dataset?

The fully annotated dataset with all information needs, german and english turns (translated with DeepL) is here: annotation/corpus/cookversational_search_dataset

AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

AugMix Introduction We propose AugMix, a data processing technique that mixes augmented images and enforces consistent embeddings of the augmented ima

Google Research 876 Dec 17, 2022
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes

FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes This repository contains the source code accompanying the paper: FlexConv: C

Robert-Jan Bruintjes 96 Dec 12, 2022
dataset for ECCV 2020 "Motion Capture from Internet Videos"

Motion Capture from Internet Videos Motion Capture from Internet Videos Junting Dong*, Qing Shuai*, Yuanqing Zhang, Xian Liu, Xiaowei Zhou, Hujun Bao

ZJU3DV 98 Dec 07, 2022
KDD CUP 2020 Automatic Graph Representation Learning: 1st Place Solution

KDD CUP 2020: AutoGraph Team: aister Members: Jianqiang Huang, Xingyuan Tang, Mingjian Chen, Jin Xu, Bohang Zheng, Yi Qi, Ke Hu, Jun Lei Team Introduc

96 May 30, 2022
PyTorch implementation of DeepLab v2 on COCO-Stuff / PASCAL VOC

DeepLab with PyTorch This is an unofficial PyTorch implementation of DeepLab v2 [1] with a ResNet-101 backbone. COCO-Stuff dataset [2] and PASCAL VOC

Kazuto Nakashima 995 Jan 08, 2023
Boundary-preserving Mask R-CNN (ECCV 2020)

BMaskR-CNN This code is developed on Detectron2 Boundary-preserving Mask R-CNN ECCV 2020 Tianheng Cheng, Xinggang Wang, Lichao Huang, Wenyu Liu Video

Hust Visual Learning Team 178 Nov 28, 2022
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR 2018).

Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR2018) By Zilong Huang, Xinggang Wang, Jiasi Wang, Wenyu Liu and J

Zilong Huang 245 Dec 13, 2022
Stratified Transformer for 3D Point Cloud Segmentation (CVPR 2022)

Stratified Transformer for 3D Point Cloud Segmentation Xin Lai*, Jianhui Liu*, Li Jiang, Liwei Wang, Hengshuang Zhao, Shu Liu, Xiaojuan Qi, Jiaya Jia

DV Lab 195 Jan 01, 2023
paper list in the area of reinforcenment learning for recommendation systems

paper list in the area of reinforcenment learning for recommendation systems

HenryZhao 23 Jun 09, 2022
Augmented Traffic Control: A tool to simulate network conditions

Augmented Traffic Control Full documentation for the project is available at http://facebook.github.io/augmented-traffic-control/. Overview Augmented

Meta Archive 4.3k Jan 08, 2023
Lbl2Vec learns jointly embedded label, document and word vectors to retrieve documents with predefined topics from an unlabeled document corpus.

Lbl2Vec Lbl2Vec is an algorithm for unsupervised document classification and unsupervised document retrieval. It automatically generates jointly embed

sebis - TUM - Germany 61 Dec 20, 2022
BackgroundRemover lets you Remove Background from images and video with a simple command line interface

BackgroundRemover BackgroundRemover is a command line tool to remove background from video and image, made by nadermx to power https://BackgroundRemov

Johnathan Nader 1.7k Dec 30, 2022
Read number plates with https://platerecognizer.com/

HASS-plate-recognizer Read vehicle license plates with https://platerecognizer.com/ which offers free processing of 2500 images per month. You will ne

Robin 69 Dec 30, 2022
Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks

SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks

Feng 2 Nov 19, 2021
Code for IntraQ, PyTorch implementation of our paper under review

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7

1 Nov 19, 2021
MAg: a simple learning-based patient-level aggregation method for detecting microsatellite instability from whole-slide images

MAg Paper Abstract File structure Dataset prepare Data description How to use MAg? Why not try the MAg_lib! Trained models Experiment and results Some

Calvin Pang 3 Apr 08, 2022
Code related to the manuscript "Averting A Crisis In Simulation-Based Inference"

Abstract We present extensive empirical evidence showing that current Bayesian simulation-based inference algorithms are inadequate for the falsificat

Montefiore Artificial Intelligence Research 3 Nov 14, 2022
Offcial repository for the IEEE ICRA 2021 paper Auto-Tuned Sim-to-Real Transfer.

Offcial repository for the IEEE ICRA 2021 paper Auto-Tuned Sim-to-Real Transfer.

47 Jun 30, 2022
Keqing Chatbot With Python

KeqingChatbot A public running instance can be found on telegram as @keqingchat_bot. Requirements Python 3.8 or higher. A bot token. Local Deploy git

Rikka-Chan 2 Jan 16, 2022
Implementation for the "Surface Reconstruction from 3D Line Segments" paper.

Surface Reconstruction from 3D Line Segments Surface reconstruction from 3d line segments. Langlois, P. A., Boulch, A., & Marlet, R. In 2019 Internati

85 Jan 04, 2023