Search Results for author:
Found 15 papers, 0 papers with code
The Effect of Data Partitioning Strategy on Model Generalizability: A Case Study of Morphological Segmentation
Recent work to enhance data partitioning strategies for more realistic model evaluation face challenges in providing a clear optimal choice.
Can Similarity-Based Domain-Ordering Reduce Catastrophic Forgetting for Intent Recognition?
While existing dialogue systems research has explored replay-based and regularization-based methods to this end, the effect of domain ordering on the CL performance of intent recognition models remains unexplored.
SPLAIN: Augmenting CybersecurityWarnings with Reasons and Data
Effective cyber threat recognition and prevention demand comprehensible forecasting systems, as prior approaches commonly offer limited and, ultimately, unconvincing information.
Agreement Tracking for Multi-Issue Negotiation Dialogues
We present a strong initial baseline for our task by transfer-learning a T5 model trained on the MultiWOZ 2. 4 corpus.
LonXplain: Lonesomeness as a Consequence of Mental Disturbance in Reddit Posts
Social media is a potential source of information that infers latent mental states through Natural Language Processing (NLP).
Exploiting Explainability to Design Adversarial Attacks and Evaluate Attack Resilience in Hate-Speech Detection Models
Our study evaluates the resilience of these models against adversarial attacks using explainability techniques.
Active Defense Against Social Engineering: The Case for Human Language Technology
We describe a system that supports natural language processing (NLP) components for active defenses against social engineering attacks.
Adaptation of a Lexical Organization for Social Engineering Detection and Response Generation
We present a paradigm for extensible lexicon development based on Lexical Conceptual Structure to support social engineering detection and response generation.
The Panacea Threat Intelligence and Active Defense Platform
We describe Panacea, a system that supports natural language processing (NLP) components for active defenses against social engineering attacks.
Detecting Asks in SE attacks: Impact of Linguistic and Structural Knowledge
Social engineers attempt to manipulate users into undertaking actions such as downloading malware by clicking links or providing access to money or sensitive information.
Use of Modality and Negation in Semantically-Informed Syntactic MT
We apply our MN annotation scheme to statistical machine translation using a syntactic framework that supports the inclusion of semantic annotations.
A Modality Lexicon and its use in Automatic Tagging
Specifically, we describe the construction of a modality annotation scheme, a modality lexicon, and two automated modality taggers that were built using the lexicon and annotation scheme.
Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach
We describe a unified and coherent syntactic framework for supporting a semantically-informed syntactic approach to statistical machine translation.
Computing Lexical Contrast
We then present an automatic and empirical measure of lexical contrast that relies on the contrast hypothesis, corpus statistics, and the structure of a {\it Roget}-like thesaurus.
