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Found 6 papers, 0 papers with code
Learning Domain-Specific Word Embeddings from Sparse Cybersecurity Texts
In this pa-per, we describe a novel method to train domain-specificword embeddings from sparse texts.
UMBC at SemEval-2018 Task 8: Understanding Text about Malware
We describe the systems developed by the UMBC team for 2018 SemEval Task 8, SecureNLP (Semantic Extraction from CybersecUrity REports using Natural Language Processing).
Predicting Malware Attributes from Cybersecurity Texts
Text analytics is a useful tool for studying malware behavior and tracking emerging threats.
Supervising Unsupervised Open Information Extraction Models
We propose a novel supervised open information extraction (Open IE) framework that leverages an ensemble of unsupervised Open IE systems and a small amount of labeled data to improve system performance.
Ghosts of NEID's Past
The NEID spectrograph is a R $\sim$ 120, 000 resolution fiber-fed and highly stabilized spectrograph for extreme radial velocity (RV) precision.
Instrumentation and Methods for Astrophysics Earth and Planetary Astrophysics
Incorporating medical knowledge in BERT for clinical relation extraction
In recent years pre-trained language models (PLM) such as BERT have proven to be very effective in diverse NLP tasks such as Information Extraction, Sentiment Analysis and Question Answering.
