Lai, Tuan, Ji, Heng, and Zhai, ChengXiang. BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Residual Convolutional Neural Networks. Retrieved from https://par.nsf.gov/biblio/10337684. Proc. The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP2021) Findings . Web. doi:10.18653/v1/2021.findings-emnlp.140.

Lai, Tuan, Ji, Heng, & Zhai, ChengXiang. BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Residual Convolutional Neural Networks. Proc. The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP2021) Findings, (). Retrieved from https://par.nsf.gov/biblio/10337684. https://doi.org/10.18653/v1/2021.findings-emnlp.140

Lai, Tuan, Ji, Heng, and Zhai, ChengXiang. "BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Residual Convolutional Neural Networks". Proc. The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP2021) Findings (). Country unknown/Code not available. https://doi.org/10.18653/v1/2021.findings-emnlp.140. https://par.nsf.gov/biblio/10337684.

@article{osti_10337684,
place = {Country unknown/Code not available}, title = {BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Residual Convolutional Neural Networks}, url = {https://par.nsf.gov/biblio/10337684}, DOI = {10.18653/v1/2021.findings-emnlp.140}, abstractNote = {}, journal = {Proc. The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP2021) Findings}, author = {Lai, Tuan and Ji, Heng and Zhai, ChengXiang}, }