Search Results for author: Akhila Yerukola

Found 6 papers, 1 papers with code

COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statements

no code implementations3 Jun 2023 Xuhui Zhou, Hao Zhu, Akhila Yerukola, Thomas Davidson, Jena D. Hwang, Swabha Swayamdipta, Maarten Sap

To study the contextual dynamics of offensiveness, we train models to generate COBRA explanations, with and without access to the context.

Don't Take This Out of Context! On the Need for Contextual Models and Evaluations for Stylistic Rewriting

no code implementations24 May 2023 Akhila Yerukola, Xuhui Zhou, Maarten Sap

Most existing stylistic text rewriting methods operate on a sentence level, but ignoring the broader context of the text can lead to generic, ambiguous, and incoherent rewrites.

Explainable Slot Type Attentions to Improve Joint Intent Detection and Slot Filling

no code implementations19 Oct 2022 Kalpa Gunaratna, Vijay Srinivasan, Akhila Yerukola, Hongxia Jin

In this work, we propose a novel approach that: (i) learns to generate additional slot type specific features in order to improve accuracy and (ii) provides explanations for slot filling decisions for the first time in a joint NLU model.

Intent Detection Natural Language Understanding +2

Data Augmentation for Voice-Assistant NLU using BERT-based Interchangeable Rephrase

no code implementations EACL 2021 Akhila Yerukola, Mason Bretan, Hongxia Jin

We introduce a data augmentation technique based on byte pair encoding and a BERT-like self-attention model to boost performance on spoken language understanding tasks.

Data Augmentation intent-classification +5

Do Massively Pretrained Language Models Make Better Storytellers?

1 code implementation CONLL 2019 Abigail See, Aneesh Pappu, Rohun Saxena, Akhila Yerukola, Christopher D. Manning

Large neural language models trained on massive amounts of text have emerged as a formidable strategy for Natural Language Understanding tasks.

Natural Language Understanding Story Generation

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