7 citations · 17 across the 5 of their papers we have counts for
6 papers · 1 filter
Improving Top-K Decoding for Non-Autoregressive Semantic Parsing via Intent Conditioning
Geunseob Oh, Rahul Goel, Chris Hidey +4
Semantic parsing (SP) is a core component of modern virtual assistants like Google Assistant and Amazon Alexa. While sequence-to-sequence-based auto-regressive (AR) approaches are…
ENTRUST: Argument Reframing with Language Models and Entailment
Tuhin Chakrabarty, Christopher Hidey, Smaranda Muresan
Framing involves the positive or negative presentation of an argument or issue depending on the audience and goal of the speaker (Entman 1983). Differences in lexical framing, the…
AMPERSAND: Argument Mining for PERSuAsive oNline Discussions
Tuhin Chakrabarty, Christopher Hidey, Smaranda Muresan +2
Argumentation is a type of discourse where speakers try to persuade their audience about the reasonableness of a claim by presenting supportive arguments. Most work in argument min…
DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking
Christopher Hidey, Tuhin Chakrabarty, Tariq Alhindi +4
The increased focus on misinformation has spurred development of data and systems for detecting the veracity of a claim as well as retrieving authoritative evidence. The Fact Extra…
IMHO Fine-Tuning Improves Claim Detection
Tuhin Chakrabarty, Christopher Hidey, Kathleen McKeown
Claims are the central component of an argument. Detecting claims across different domains or data sets can often be challenging due to their varying conceptualization. We propose…
Leveraging Sparse and Dense Feature Combinations for Sentiment Classification
Tao Yu, Christopher Hidey, Owen Rambow +1
Neural networks are one of the most popular approaches for many natural language processing tasks such as sentiment analysis. They often outperform traditional machine learning mod…