%0 Conference Paper %1 conf/ijcnn/LiuCMC23 %A Liu, Ruicheng %A Chen, Guanyi %A Mao, Rui %A Cambria, Erik %B IJCNN %D 2023 %I IEEE %K dblp %P 1-8 %T A Multi-task Learning Model for Gold-two-mention Co-reference Resolution. %U http://dblp.uni-trier.de/db/conf/ijcnn/ijcnn2023.html#LiuCMC23 %@ 978-1-6654-8867-9

@inproceedings{conf/ijcnn/LiuCMC23, added-at = {2024-05-07T00:00:00.000+0200}, author = {Liu, Ruicheng and Chen, Guanyi and Mao, Rui and Cambria, Erik}, biburl = {https://www.bibsonomy.org/bibtex/267a14fbf5497937aa85cb00ead741aab/dblp}, booktitle = {IJCNN}, crossref = {conf/ijcnn/2023}, ee = {https://doi.org/10.1109/IJCNN54540.2023.10191719}, interhash = {ceada6b802dee75b6e3d81cdfcd12e3d}, intrahash = {67a14fbf5497937aa85cb00ead741aab}, isbn = {978-1-6654-8867-9}, keywords = {dblp}, pages = {1-8}, publisher = {IEEE}, timestamp = {2024-05-13T09:01:38.000+0200}, title = {A Multi-task Learning Model for Gold-two-mention Co-reference Resolution.}, url = {http://dblp.uni-trier.de/db/conf/ijcnn/ijcnn2023.html#LiuCMC23}, year = 2023 }