Search Results for author:
Found 16 papers, 7 papers with code
SemLink 2.0: Chasing Lexical Resources
The SemLink resource provides mappings between a variety of lexical semantic ontologies, each with their strengths and weaknesses.
IMPLI: Investigating NLI Models’ Performance on Figurative Language
Natural language inference (NLI) has been widely used as a task to train and evaluate models for language understanding.
Exploring Metaphoric Paraphrase Generation
Metaphor generation is a difficult task, and has seen tremendous improvement with the advent of deep pretrained models.
Identifying Fairness Issues in Automatically Generated Testing Content
Natural language generation tools are powerful and effective for generating content.
Lessons Learned from a Citizen Science Project for Natural Language Processing
Citizen Science is an alternative to crowdsourcing that is relatively unexplored in the context of NLP.
Controlled Language Generation for Language Learning Items
This work aims to employ natural language generation (NLG) to rapidly generate items for English language learning applications: this requires both language models capable of generating fluent, high-quality English, and to control the output of the generation to match the requirements of the relevant items.
Metaphor Generation with Conceptual Mappings
Guided by conceptual metaphor theory, we propose to control the generation process by encoding conceptual mappings between cognitive domains to generate meaningful metaphoric expressions.
The challenges of temporal alignment on Twitter during crises
Language use changes over time, and this impacts the effectiveness of NLP systems.
Ranking Creative Language Characteristics in Small Data Scenarios
We therefore adapt the DirectRanker to provide a new deep model for ranking creative language with small data.
Metaphoric Paraphrase Generation
This work describes the task of metaphoric paraphrase generation, in which we are given a literal sentence and are charged with generating a metaphoric paraphrase.
Linguistic Analysis Improves Neural Metaphor Detection
In the field of metaphor detection, deep learning systems are the ubiquitous and achieve strong performance on many tasks.
Developing and Evaluating Annotation Procedures for Twitter Data during Hazard Events
As social media grows more popular, an increasing number of people are using social media platforms to obtain and share information about approaching threats and discuss their interpretations of the threat and their protective decisions.
Improving Classification of Twitter Behavior During Hurricane Events
We show that feature-based and deep learning methods provide different benefits for tweet classification, and ensemble-based methods using linguistic, temporal, and geospatial features can effectively classify user behavior.
Leveraging Syntactic Constructions for Metaphor Identification
Identification of metaphoric language in text is critical for generating effective semantic representations for natural language understanding.
