Search Results for author: Christopher Hidey

Found 14 papers, 6 papers with code

Reducing Model Churn: Stable Re-training of Conversational Agents

1 code implementation SIGDIAL (ACL) 2022 Christopher Hidey, Fei Liu, Rahul Goel

Lastly, we discuss practical trade-offs between such techniques and show that co-distillation provides a sweet spot in terms of churn reduction with only a modest increase in resource usage.

Semantic Parsing Structured Prediction

DAMP: Doubly Aligned Multilingual Parser for Task-Oriented Dialogue

1 code implementation15 Dec 2022 William Held, Christopher Hidey, Fei Liu, Eric Zhu, Rahul Goel, Diyi Yang, Rushin Shah

Modern virtual assistants use internal semantic parsing engines to convert user utterances to actionable commands.

Semantic Parsing XLM-R

Reducing Model Jitter: Stable Re-training of Semantic Parsers in Production Environments

no code implementations10 Apr 2022 Christopher Hidey, Fei Liu, Rahul Goel

Lastly, we discuss practical trade-offs between such techniques and show that co-distillation provides a sweet spot in terms of jitter reduction for semantic parsing systems with only a modest increase in resource usage.

Semantic Parsing

ENTRUST: Argument Reframing with Language Models and Entailment

no code implementations NAACL 2021 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).

Text Generation

AMPERSAND: Argument Mining for PERSuAsive oNline Discussions

1 code implementation IJCNLP 2019 Tuhin Chakrabarty, Christopher Hidey, Smaranda Muresan, Kathy Mckeown, Alyssa Hwang

Our approach for relation prediction uses contextual information in terms of fine-tuning a pre-trained language model and leveraging discourse relations based on Rhetorical Structure Theory.

Argument Mining Language Modelling

DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking

1 code implementation ACL 2020 Christopher Hidey, Tuhin Chakrabarty, Tariq Alhindi, Siddharth Varia, Kriste Krstovski, Mona Diab, Smaranda Muresan

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.

Fact Checking Misinformation +1

Confirming the Non-compositionality of Idioms for Sentiment Analysis

no code implementations WS 2019 Alyssa Hwang, Christopher Hidey

An idiom is defined as a non-compositional multiword expression, one whose meaning cannot be deduced from the definitions of the component words.

Sentiment Analysis

Team SWEEPer: Joint Sentence Extraction and Fact Checking with Pointer Networks

no code implementations WS 2018 Christopher Hidey, Mona Diab

We present experiments on the FEVER (Fact Extraction and VERification) task, a shared task that involves selecting sentences from Wikipedia and predicting whether a claim is supported by those sentences, refuted, or there is not enough information.

Fact Checking Information Retrieval +6

Analyzing the Semantic Types of Claims and Premises in an Online Persuasive Forum

no code implementations WS 2017 Christopher Hidey, Elena Musi, Alyssa Hwang, Smar Muresan, a, Kathy Mckeown

Argumentative text has been analyzed both theoretically and computationally in terms of argumentative structure that consists of argument components (e. g., claims, premises) and their argumentative relations (e. g., support, attack).

Argument Mining

Leveraging Sparse and Dense Feature Combinations for Sentiment Classification

no code implementations13 Aug 2017 Tao Yu, Christopher Hidey, Owen Rambow, Kathleen McKeown

This model outperforms many deep learning models and achieves comparable results to other deep learning models with complex architectures on sentiment analysis datasets.

BIG-bench Machine Learning Classification +3

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