69 citations · 127 across the 14 of their papers we have counts for
7 papers · 1 filter
Understanding Counterspeech for Online Harm Mitigation
Yi-Ling Chung, Gavin Abercrombie, Florence Enock +2
Counterspeech offers direct rebuttals to hateful speech by challenging perpetrators of hate and showing support to targets of abuse. It provides a promising alternative to more con…
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…
Mirages: On Anthropomorphism in Dialogue Systems
Gavin Abercrombie, Amanda Cercas Curry, Tanvi Dinkar +2
Automated dialogue or conversational systems are anthropomorphised by developers and personified by users. While a degree of anthropomorphism may be inevitable due to the choice of…
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
Anya Belz, Craig Thomson, Ehud Reiter +39
We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/le…
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…
Consistency is Key: Disentangling Label Variation in Natural Language Processing with Intra-Annotator Agreement
Gavin Abercrombie, Tanvi Dinkar, Amanda Cercas Curry +2
We commonly use agreement measures to assess the utility of judgements made by human annotators in Natural Language Processing (NLP) tasks. While inter-annotator agreement is frequ…