Search Results for author: Isabel Cachola

Found 10 papers, 5 papers with code

Model Distillation for Faithful Explanations of Medical Code Predictions

no code implementations BioNLP (ACL) 2022 Zach Wood-Doughty, Isabel Cachola, Mark Dredze

We propose to use knowledge distillation, or training a student model that mimics the behavior of a trained teacher model, as a technique to generate faithful and plausible explanations.

Decision Making Knowledge Distillation

Knowledge-Centric Templatic Views of Documents

no code implementations13 Jan 2024 Isabel Cachola, Silviu Cucerzan, Allen herring, Vuksan Mijovic, Erik Oveson, Sujay Kumar Jauhar

Thus, in our work, we consider each of these documents to be templatic views of the same underlying knowledge, and we aim to unify the generation and evaluation of these templatic views of documents.

Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models

no code implementations14 Nov 2023 Carlos Aguirre, Kuleen Sasse, Isabel Cachola, Mark Dredze

In this work, we explore the effect of shots, which directly affect the performance of models, on the fairness of LLMs as NLP classification systems.

Fairness Few-Shot Learning +1

Faithful and Plausible Explanations of Medical Code Predictions

1 code implementation16 Apr 2021 Zach Wood-Doughty, Isabel Cachola, Mark Dredze

Machine learning models that offer excellent predictive performance often lack the interpretability necessary to support integrated human machine decision-making.

Decision Making

Why Swear? Analyzing and Inferring the Intentions of Vulgar Expressions

no code implementations EMNLP 2018 Eric Holgate, Isabel Cachola, Daniel Preo{\c{t}}iuc-Pietro, Junyi Jessy Li

Vulgar words are employed in language use for several different functions, ranging from expressing aggression to signaling group identity or the informality of the communication.

Hate Speech Detection

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