metadata
language:
- en
config_names:
- query
- corpus
- qrels
tags:
- information-retrieval
- multimodal-retrieval
dataset_info:
- config_name: qrels
features:
- name: query-id
dtype: string
- name: Q0
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int8
splits:
- name: test
num_examples: 3609
- config_name: corpus
features:
- name: id
dtype: string
- name: modality
dtype: string
- name: text
dtype: string
- name: image
dtype: image
splits:
- name: corpus
num_examples: 138794
- config_name: query
features:
- name: id
dtype: string
- name: modality
dtype: string
- name: text
dtype: string
- name: image
dtype: image
splits:
- name: test
num_examples: 3609
configs:
- config_name: qrels
data_files:
- split: test
path: qrels.parquet
- config_name: corpus
data_files:
- split: corpus
path: corpus.parquet
- config_name: query
data_files:
- split: test
path: query.parquet
license: cc0-1.0
ReMuQ Image-Text to Text Retrieval
Converted from https://github.com/luomancs/ReMuQ
@inproceedings{luo-etal-2023-end,
title = "End-to-end Knowledge Retrieval with Multi-modal Queries",
author = "Luo, Man and
Fang, Zhiyuan and
Gokhale, Tejas and
Yang, Yezhou and
Baral, Chitta",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-long.478",
doi = "10.18653/v1/2023.acl-long.478",
pages = "8573--8589",
}