Search Results for author:
Found 38 papers, 7 papers with code
On the Need for Thoughtful Data Collection for Multi-Party Dialogue: A Survey of Available Corpora and Collection Methods
We present a comprehensive survey of available corpora for multi-party dialogue.
BeSt: The Belief and Sentiment Corpus
We present the BeSt corpus, which records cognitive state: who believes what (i. e., factuality), and who has what sentiment towards what.
Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges
This is a report on the NSF Future Directions Workshop on Automatic Evaluation of Dialog.
A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspective
Then, we overview the field of conversational assistants and their applications in software engineering and education.
Can We Generate Shellcodes via Natural Language? An Empirical Study
Writing software exploits is an important practice for offensive security analysts to investigate and prevent attacks.
Ranked #1 on
Code Generation
on Shellcode_IA32
A Case Study of Analysis of Construals in Language on Social Media Surrounding a Crisis Event
The events that took place at the Unite the Right rally held in Charlottesville, Virginia on August 11-12, 2017 caused intense reaction on social media from users across the political spectrum.
Shellcode_IA32: A Dataset for Automatic Shellcode Generation
We take the first step to address the task of automatically generating shellcodes, i. e., small pieces of code used as a payload in the exploitation of a software vulnerability, starting from natural language comments.
Ranked #3 on
Code Generation
on Shellcode_IA32
TeamUNCC@LT-EDI-EACL2021: Hope Speech Detection using Transfer Learning with Transformers
We describe our approach to fine-tuning RoBERTa for Hope Speech detection in English and our approach to fine-tuning XLM-RoBERTa for Hope Speech detection in Tamil and Malayalam, two low resource Indic languages.
Ranked #1 on
Hope Speech Detection for English
on HopeEDI
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics.
Ranked #1 on
Extreme Summarization
on GEM-XSum
Abstractive Text Summarization
Cross-Lingual Abstractive Summarization
+5
Learning to Plan and Realize Separately for Open-Ended Dialogue Systems
Achieving true human-like ability to conduct a conversation remains an elusive goal for open-ended dialogue systems.
Understanding the Impact of Experiment Design for Evaluating Dialogue System Output
Evaluation of output from natural language generation (NLG) systems is typically conducted via crowdsourced human judgments.
Studying The Effect of Emotional and Moral Language on Information Contagion during the Charlottesville Event
We highlight the contribution of emotional and moral language towards information contagion online.
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.
Studying the Effects of Cognitive Biases in Evaluation of Conversational Agents
To investigate, we conducted a between-subjects study with 77 crowdsourced workers to understand the role of cognitive biases, specifically anchoring bias, when humans are asked to evaluate the output of conversational agents.
Natural Language Generation Using Reinforcement Learning with External Rewards
We propose an approach towards natural language generation using a bidirectional encoder-decoder which incorporates external rewards through reinforcement learning (RL).
Emotional Neural Language Generation Grounded in Situational Contexts
Emotional language generation is one of the keys to human-like artificial intelligence.
JUSTDeep at NLP4IF 2019 Task 1: Propaganda Detection using Ensemble Deep Learning Models
Defining {``}fake news{''} is not well established yet, however, it can be categorized under several labels: false, biased, or framed to mislead the readers that are characterized as propaganda.
Towards Best Experiment Design for Evaluating Dialogue System Output
To overcome the limitations of automated metrics (e. g. BLEU, METEOR) for evaluating dialogue systems, researchers typically use human judgments to provide convergent evidence.
Emoji Usage Across Platforms: A Case Study for the Charlottesville Event
We study emoji usage patterns across two social media platforms, one of them considered a fringe community called Gab, and the other Twitter.
I Stand With You: Using Emojis to Study Solidarity in Crisis Events
We study how emojis are used to express solidarity in social media in the context of two major crisis events - a natural disaster, Hurricane Irma in 2017 and terrorist attacks that occurred on November 2015 in Paris.
A Survey of Natural Language Generation Techniques with a Focus on Dialogue Systems - Past, Present and Future Directions
We provide a comprehensive review towards building open domain dialogue systems, an important application of natural language generation.
TeamUNCC at SemEval-2018 Task 1: Emotion Detection in English and Arabic Tweets using Deep Learning
This paper describes TeamUNCC{'}s system to detect emotions in English and Arabic tweets.
The Validation of MRCPD Cross-language Expansions on Imageability Ratings
In this article, we present a method to validate a multi-lingual (English, Spanish, Russian, and Farsi) corpus on imageability ratings automatically expanded from MRCPD (Liu et al., 2014).
ANEW+: Automatic Expansion and Validation of Affective Norms of Words Lexicons in Multiple Languages
The main contributions of this work are: 1) A general method for expansion and creation of lexicons with scores of words on psychological constructs such as valence, arousal or dominance; and 2) a procedure for ensuring validity of the newly constructed resources.
A Multi-Cultural Repository of Automatically Discovered Linguistic and Conceptual Metaphors
Researchers in the field can use this resource as a reference of typical metaphors used across these cultures.
Automatic Expansion of the MRC Psycholinguistic Database Imageability Ratings
Unfortunately, word imageability ratings were collected for only a limited number of words: 9, 240 words in English, 6, 233 in Spanish; and are unavailable at all in the other two languages studied: Russian and Farsi.
Extending the MPC corpus to Chinese and Urdu - A Multiparty Multi-Lingual Chat Corpus for Modeling Social Phenomena in Language
In this paper, we report our efforts in building a multi-lingual multi-party online chat corpus in order to develop a firm understanding in a set of social constructs such as agenda control, influence, and leadership as well as to computationally model such constructs in online interactions.
Revealing Contentious Concepts Across Social Groups
The hypothesis of this work is that there are communities or groups which can be characterized by a network of concepts and the corresponding valuations of those concepts that are agreed upon by the members of the community.
