Search Results for author: Aoife Cahill

Found 36 papers, 2 papers with code

A New Task and Dataset on Detecting Attacks on Human Rights Defenders

1 code implementation30 Jun 2023 Shihao Ran, Di Lu, Joel Tetreault, Aoife Cahill, Alejandro Jaimes

The ability to conduct retrospective analyses of attacks on human rights defenders over time and by location is important for humanitarian organizations to better understand historical or ongoing human rights violations and thus better manage the global impact of such events.

Humanitarian

Context-based Automated Scoring of Complex Mathematical Responses

no code implementations WS 2020 Aoife Cahill, James H Fife, Brian Riordan, Avijit Vajpayee, Dmytro Galochkin

The tasks of automatically scoring either textual or algebraic responses to mathematical questions have both been well-studied, albeit separately.

Explainable Models

Automated Scoring: Beyond Natural Language Processing

no code implementations COLING 2018 Nitin Madnani, Aoife Cahill

In this position paper, we argue that building operational automated scoring systems is a task that has disciplinary complexity above and beyond standard competitive shared tasks which usually involve applying the latest machine learning techniques to publicly available data in order to obtain the best accuracy.

BIG-bench Machine Learning Position +1

A Large Scale Quantitative Exploration of Modeling Strategies for Content Scoring

no code implementations WS 2017 Nitin Madnani, Anastassia Loukina, Aoife Cahill

We explore various supervised learning strategies for automated scoring of content knowledge for a large corpus of 130 different content-based questions spanning four subject areas (Science, Math, English Language Arts, and Social Studies) and containing over 230, 000 responses scored by human raters.

Math

Speech- and Text-driven Features for Automated Scoring of English Speaking Tasks

no code implementations WS 2017 Anastassia Loukina, Nitin Madnani, Aoife Cahill

We consider the automatic scoring of a task for which both the content of the response as well its spoken fluency are important.

Automatic Speech Recognition (ASR)

Building Better Open-Source Tools to Support Fairness in Automated Scoring

no code implementations WS 2017 Nitin Madnani, Anastassia Loukina, Alina von Davier, Jill Burstein, Aoife Cahill

Automated scoring of written and spoken responses is an NLP application that can significantly impact lives especially when deployed as part of high-stakes tests such as the GRE® and the TOEFL®.

Fairness Test

Cannot find the paper you are looking for? You can Submit a new open access paper.