no code implementations • EMNLP (ClinicalNLP) 2020 • Wenjie Wang, Youngja Park, Taesung Lee, Ian Molloy, Pengfei Tang, Li Xiong
Among the modalities of medical data, the clinical summaries have higher risks to be attacked because they are generated by third-party companies.
no code implementations • 30 Jan 2024 • Shrayani Mondal, Rishabh Garodia, Arbaaz Qureshi, Taesung Lee, Youngja Park
We leverage the potential of generative language models to discover human-interpretable descriptors present in a dataset and use an unsupervised approach to explain neurons with these descriptors.
1 code implementation • 30 Oct 2023 • Jatin Arora, Youngja Park
In this work, we address the NER problem by splitting it into two logical sub-tasks: (1) Span Detection which simply extracts entity mention spans irrespective of entity type; (2) Span Classification which classifies the spans into their entity types.
1 code implementation • 1 Nov 2022 • Md Tanvirul Alam, Dipkamal Bhusal, Youngja Park, Nidhi Rastogi
The framework characterizes attack patterns by capturing the phases of an attack in Android and enterprise networks and systematically maps them to the MITRE ATT\&CK pattern framework.
1 code implementation • 8 Apr 2022 • Md Tanvirul Alam, Dipkamal Bhusal, Youngja Park, Nidhi Rastogi
Open Cyber threat intelligence (OpenCTI) information is available in an unstructured format from heterogeneous sources on the Internet.
no code implementations • 3 Sep 2021 • Ryan Christian, Sharmishtha Dutta, Youngja Park, Nidhi Rastogi
This ontology forms the basis for the malware threat intelligence knowledge graph, MalKG, which we exemplify using three different, non-overlapping demonstrations.
no code implementations • 11 Jun 2020 • Kathrin Grosse, Taesung Lee, Battista Biggio, Youngja Park, Michael Backes, Ian Molloy
Backdoor attacks mislead machine-learning models to output an attacker-specified class when presented a specific trigger at test time.
no code implementations • IJCNLP 2019 • Arpita Roy, Youngja Park, Taesung Lee, SHimei Pan
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.
no code implementations • NAACL 2019 • Arpita Roy, Youngja Park, SHimei Pan
Text analytics is a useful tool for studying malware behavior and tracking emerging threats.
no code implementations • SEMEVAL 2018 • Ankur Padia, Arpita Roy, Taneeya Satyapanich, Francis Ferraro, SHimei Pan, Youngja Park, Anupam Joshi, Tim Finin
We describe the systems developed by the UMBC team for 2018 SemEval Task 8, SecureNLP (Semantic Extraction from CybersecUrity REports using Natural Language Processing).
no code implementations • ICLR 2018 • Taesung Lee, Youngja Park
We present a new unsupervised method for learning general-purpose sentence embeddings.
no code implementations • 21 Sep 2017 • Arpita Roy, Youngja Park, SHimei Pan
In this pa-per, we describe a novel method to train domain-specificword embeddings from sparse texts.
no code implementations • 12 Nov 2013 • Shandian Zhe, Yuan Qi, Youngja Park, Ian Molloy, Suresh Chari
To overcome this limitation, we present Distributed Infinite Tucker (DINTUCKER), a large-scale nonlinear tensor decomposition algorithm on MAPREDUCE.