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20172022
most citedLaMDA: Language Models for Dialog Applications

708 citations · 1.2k across the 14 of their papers we have counts for

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11 papers · 1 filter

cs.CL20222 cited

Cultural Re-contextualization of Fairness Research in Language Technologies in India

Shaily Bhatt, Sunipa Dev, Partha Talukdar +2

Recent research has revealed undesirable biases in NLP data and models. However, these efforts largely focus on social disparities in the West, and are not directly portable to oth…

cs.CL2022708 cited

LaMDA: Language Models for Dialog Applications

Romal Thoppilan, Daniel De Freitas, Jamie Hall +57

We present LaMDA: Language Models for Dialog Applications. LaMDA is a family of Transformer-based neural language models specialized for dialog, which have up to 137B parameters an…

cs.CL20213 cited

Dealing with Disagreements: Looking Beyond the Majority Vote in Subjective Annotations

Aida Mostafazadeh Davani, Mark Díaz, Vinodkumar Prabhakaran

Majority voting and averaging are common approaches employed to resolve annotator disagreements and derive single ground truth labels from multiple annotations. However, annotators…

cs.CL2021

On Releasing Annotator-Level Labels and Information in Datasets

Vinodkumar Prabhakaran, Aida Mostafazadeh Davani, Mark Díaz

A common practice in building NLP datasets, especially using crowd-sourced annotations, involves obtaining multiple annotator judgements on the same data instances, which are then…

cs.CL2021

How Metaphors Impact Political Discourse: A Large-Scale Topic-Agnostic Study Using Neural Metaphor Detection

Vinodkumar Prabhakaran, Marek Rei, Ekaterina Shutova

Metaphors are widely used in political rhetoric as an effective framing device. While the efficacy of specific metaphors such as the war metaphor in political discourse has been do…

cs.CL2021

Detecting Cross-Geographic Biases in Toxicity Modeling on Social Media

Sayan Ghosh, Dylan Baker, David Jurgens +1

Online social media platforms increasingly rely on Natural Language Processing (NLP) techniques to detect abusive content at scale in order to mitigate the harms it causes to their…