2 papers
cs.CL2024
Hybrid X-Linker: Automated Data Generation and Extreme Multi-label Ranking for Biomedical Entity Linking
Pedro Ruas, Fernando Gallego, Francisco J. Veredas +1
State-of-the-art deep learning entity linking methods rely on extensive human-labelled data, which is costly to acquire. Current datasets are limited in size, leading to inadequate…
cs.CL2023
LASIGE and UNICAGE solution to the NASA LitCoin NLP Competition
Pedro Ruas, Diana F. Sousa, André Neves +2
Biomedical Natural Language Processing (NLP) tends to become cumbersome for most researchers, frequently due to the amount and heterogeneity of text to be processed. To address thi…