16 citations · 34 across the 9 of their papers we have counts for
9 papers · 1 filter
NLP for Counterspeech against Hate: A Survey and How-To Guide
Helena Bonaldi, Yi-Ling Chung, Gavin Abercrombie +1
In recent years, counterspeech has emerged as one of the most promising strategies to fight online hate. These non-escalatory responses tackle online abuse while preserving the fre…
Subjective ? On the Danger of Conflating Hate and Offence in Abusive Language Detection
Amanda Cercas Curry, Gavin Abercrombie, Zeerak Talat
Natural language processing research has begun to embrace the notion of annotator subjectivity, motivated by variations in labelling. This approach understands each annotator's vie…
On the Origins of Bias in NLP through the Lens of the Jim Code
Fatma Elsafoury, Gavin Abercrombie
In this paper, we trace the biases in current natural language processing (NLP) models back to their origins in racism, sexism, and homophobia over the last 500 years. We review li…
iLab at SemEval-2023 Task 11 Le-Wi-Di: Modelling Disagreement or Modelling Perspectives?
Nikolas Vitsakis, Amit Parekh, Tanvi Dinkar +3
There are two competing approaches for modelling annotator disagreement: distributional soft-labelling approaches (which aim to capture the level of disagreement) or modelling pers…
SemEval-2023 Task 11: Learning With Disagreements (LeWiDi)
Elisa Leonardelli, Alexandra Uma, Gavin Abercrombie +6
NLP datasets annotated with human judgments are rife with disagreements between the judges. This is especially true for tasks depending on subjective judgments such as sentiment an…
Risk-graded Safety for Handling Medical Queries in Conversational AI
Gavin Abercrombie, Verena Rieser
Conversational AI systems can engage in unsafe behaviour when handling users' medical queries that can have severe consequences and could even lead to deaths. Systems therefore nee…