Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering.

Sebastian Hofstätter|Markus Zlabinger|Mete Sertkan|Michael Schröder|Allan Hanbury


Anthology ID:DBLP:conf/cikm/HofstatterZSSH20
Volume:CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020
Year:2020
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:3031-3038
URL:https://doi.org/10.1145/3340531.3412878
DOI:https://doi.org/10.1145/3340531.3412878
DBLP:conf/cikm/HofstatterZSSH20
BibTeX:
@inproceedings{hofstatter-2020-finegrained, author = {Sebastian Hofst\"{a}tter and Markus Zlabinger and Mete Sertkan and Michael Schr\"{o}der and Allan Hanbury}, editor = {Mathieu d'Aquin and Stefan Dietze and Claudia Hauff and Edward Curry and Philippe Cudr\'{e}-Mauroux}, title = {{Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering}}, booktitle = {{CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020}}, pages = {3031--3038}, publisher = {ACM}, year = {2020}, url = {https://doi.org/10.1145/3340531.3412878}, doi = {https://doi.org/10.1145/3340531.3412878} }