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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). We participated in three of the sub-tasks: (1) ...
A Unified Bayesian Model of Scripts, Frames and Language
(AAAI Press, 2016-02-12)
We present the first probabilistic model to capture all levels of the Minsky Frame structure, with the goal of corpus-based induction of scenario definitions. Our model unifies prior efforts in discourse-level modeling ...
Team UMBC-FEVER: Claim verification using Semantic Lexical Resources
We describe our system used in the 2018 FEVER shared task. The system employed a frame-based information retrieval approach to select Wikipedia sentences providing evidence and used a two-layer multilayer perceptron to ...
¿Es un platano? Exploring the Application of a Physically Grounded Language Acquisition System to Spanish
(Association for Computational Linguistics, 2019-06)
In this paper we describe a multilingual grounded language learning system adapted from an English-only system. This system learns the meaning of words used in crowd-sourced descriptions by grounding them in the physical ...