7 citations · 20 across the 7 of their papers we have counts for
8 papers
DAMP: Doubly Aligned Multilingual Parser for Task-Oriented Dialogue
William Held, Christopher Hidey, Fei Liu +4
Modern virtual assistants use internal semantic parsing engines to convert user utterances to actionable commands. However, prior work has demonstrated that semantic parsing is a d…
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…
Reducing Model Jitter: Stable Re-training of Semantic Parsers in Production Environments
Christopher Hidey, Fei Liu, Rahul Goel
Retraining modern deep learning systems can lead to variations in model performance even when trained using the same data and hyper-parameters by simply using different random seed…
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…