ArchivalQA: A Large-scale Benchmark Dataset for Open-Domain Question Answering over Historical News Collections.
Jiexin Wang|Adam Jatowt|Masatoshi Yoshikawa
| Anthology ID: | DBLP:conf/sigir/WangJY22 |
|---|---|
| Volume: | SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022 |
| Year: | 2022 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 3025-3035 |
| URL: | https://doi.org/10.1145/3477495.3531734 |
| DOI: | https://doi.org/10.1145/3477495.3531734 |
| DBLP: | conf/sigir/WangJY22 |
| BibTeX: |
@inproceedings{wang-2022-archivalqa,
author = {Jiexin Wang and
Adam Jatowt and
Masatoshi Yoshikawa},
editor = {Enrique Amig\'{o} and
Pablo Castells and
Julio Gonzalo and
Ben Carterette and
J. Shane Culpepper and
Gabriella Kazai},
title = {{ArchivalQA: A Large-scale Benchmark Dataset for Open-Domain Question Answering over Historical News Collections}},
booktitle = {{SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022}},
pages = {3025--3035},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3477495.3531734},
doi = {https://doi.org/10.1145/3477495.3531734}
}