Deep Learning solutions based on fixed contextualized embeddings from PubMedBERT on BioASQ 10b and traditional IR in Synergy.

@inproceedings{almeida-2022-deep, author = {Tiago Melo Almeida and Andr\'{e} Pinho and Rodrigo Pereira and S\'{e}rgio Matos}, editor = {Guglielmo Faggioli and Nicola Ferro and Allan Hanbury and Martin Potthast}, title = {{Deep Learning solutions based on fixed contextualized embeddings from PubMedBERT on BioASQ 10b and traditional IR in Synergy}}, booktitle = {{Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum, Bologna, Italy, September 5th - to - 8th, 2022}}, series = {CEUR Workshop Proceedings}, volume = {3180}, pages = {204--221}, publisher = {CEUR-WS.org}, year = {2022}, url = {https://ceur-ws.org/Vol-3180/paper-12.pdf} }