Search Results for author:
Found 8 papers, 3 papers with code
Modeling Human Mental States with an Entity-based Narrative Graph
Understanding narrative text requires capturing characters' motivations, goals, and mental states.
Weakly-Supervised Modeling of Contextualized Event Embedding for Discourse Relations
Representing, and reasoning over, long narratives requires models that can deal with complex event structures connected through multiple relationship types.
Attention-Based Self-Supervised Feature Learning for Security Data
While applications of machine learning in cyber-security have grown rapidly, most models use manually constructed features.
ACE -- An Anomaly Contribution Explainer for Cyber-Security Applications
In this paper, we introduce Anomaly Contribution Explainer or ACE, a tool to explain security anomaly detection models in terms of the model features through a regression framework, and its variant, ACE-KL, which highlights the important anomaly contributors.
Multi-Relational Script Learning for Discourse Relations
Modeling script knowledge can be useful for a wide range of NLP tasks.
Ideological Phrase Indicators for Classification of Political Discourse Framing on Twitter
Politicians carefully word their statements in order to influence how others view an issue, a political strategy called framing.
PurdueNLP at SemEval-2017 Task 1: Predicting Semantic Textual Similarity with Paraphrase and Event Embeddings
Our proposed system consists of two subsystems and one regression model for predicting STS scores.
