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05/02/2023
Stars Are All You Need: A Distantly Supervised Pyramid Network for Document-Level End-to-End Sentiment Analysis
In this paper, we propose document-level end-to-end sentiment analysis t...
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05/20/2022
Measuring algorithmic interpretability: A human-learning-based framework and the corresponding cognitive complexity score
Algorithmic interpretability is necessary to build trust, ensure fairnes...
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03/02/2022
py-irt: A Scalable Item Response Theory Library for Python
py-irt is a Python library for fitting Bayesian Item Response Theory (IR...
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10/30/2020
Dynamic Data Selection for Curriculum Learning via Ability Estimation
Curriculum learning methods typically rely on heuristics to estimate the...
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10/09/2019
Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity
Expanding new functionalities efficiently is an ongoing challenge for si...
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08/29/2019
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds
Incorporating Item Response Theory (IRT) into NLP tasks can provide valu...
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02/27/2017
CIFT: Crowd-Informed Fine-Tuning to Improve Machine Learning Ability
Item Response Theory (IRT) allows for measuring ability of Machine Learn...
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02/15/2017
An Analysis of Ability in Deep Neural Networks
Deep neural networks (DNNs) have made significant progress in a number o...
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05/28/2016
