2024
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Can political dogwhistles be predicted by distributional methods for analysis of lexical semantic change?
Max Boholm
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Björn Rönnerstrand
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Ellen Breitholtz
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Robin Cooper
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Elina Lindgren
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Gregor Rettenegger
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Asad Sayeed
Proceedings of the 5th Workshop on Computational Approaches to Historical Language Change
2023
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Proceedings of the 15th International Conference on Computational Semantics
Maxime Amblard
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Ellen Breitholtz
Proceedings of the 15th International Conference on Computational Semantics
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Proceedings of the 2023 CLASP Conference on Learning with Small Data (LSD)
Ellen Breitholtz
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Shalom Lappin
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Sharid Loaiciga
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Nikolai Ilinykh
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Simon Dobnik
Proceedings of the 2023 CLASP Conference on Learning with Small Data (LSD)
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Because is why: Children’s acquisition of topoi through why questions
Christine Howes
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Ellen Breitholtz
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Vladislav Maraev
Proceedings of the 2023 CLASP Conference on Learning with Small Data (LSD)
In this paper we look at how children learn the underlying principles of commonsense reasoning, sometimes referred to as topoi, which are prevalent in everyday dialogue. By examining the utterances of two children in the CHILDES corpus for whom there is extensive longitudinal data, we show how children can elicit topoi from their parents by asking why-questions. This strategy for the rapid acquisition of topoi peaks at around age three, suggesting that it is a critical step in becoming a fully competent language user.
2022
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Distributional properties of political dogwhistle representations in Swedish BERT
Niclas Hertzberg
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Robin Cooper
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Elina Lindgren
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Björn Rönnerstrand
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Gregor Rettenegger
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Ellen Breitholtz
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Asad Sayeed
Proceedings of the Sixth Workshop on Online Abuse and Harms (WOAH)
“Dogwhistles” are expressions intended by the speaker have two messages: a socially-unacceptable “in-group” message understood by a subset of listeners, and a benign message intended for the out-group. We take the result of a word-replacement survey of the Swedish population intended to reveal how dogwhistles are understood, and we show that the difficulty of annotating dogwhistles is reflected in the separability in the space of a sentence-transformer Swedish BERT trained on general data.
2021
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Proceedings of the Reasoning and Interaction Conference (ReInAct 2021)
Christine Howes
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Simon Dobnik
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Ellen Breitholtz
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Stergios Chatzikyriakidis
Proceedings of the Reasoning and Interaction Conference (ReInAct 2021)
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Dogwhistles as Inferences in Interaction
Ellen Breitholtz
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Robin Cooper
Proceedings of the Reasoning and Interaction Conference (ReInAct 2021)
In this paper we will argue that the nature of dogwhistle communication is essentially dialogical, and that to account for dogwhistle meaning we must consider dialogical events in which dialogue partners can draw different conclusions based on communicative events. This leads us to a theory based on inference. However, as identified by Khoo (2017) and emphasised by Henderson & McCready (2018), a problematic aspect of this approach is that expressions that have a similar meaning are analysed as generating the same dogwhistle inferences, which appears not always to be the case. By modelling meaning in terms of intensional types in TTR, we avoid this problem.
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Why Should I Turn Left? Towards Active Explainability for Spoken Dialogue Systems.
Vladislav Maraev
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Ellen Breitholtz
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Christine Howes
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Jean-Philippe Bernardy
Proceedings of the Reasoning and Interaction Conference (ReInAct 2021)
In this paper we argue that to make dialogue systems able to actively explain their decisions they can make use of enthymematic reasoning. We motivate why this is an appropriate strategy and integrate it within our own proof-theoretic dialogue manager framework based on linear logic. In particular, this enables a dialogue system to provide reasonable answers to why-questions that query information previously given by the system.
2020
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Personae under uncertainty: The case of topoi
Bill Noble
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Ellen Breitholtz
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Robin Cooper
Proceedings of the Probability and Meaning Conference (PaM 2020)
In this paper, we propose a probabilistic model of social signalling which adopts a persona-based account of social meaning. We use this model to develop a socio-semantic theory of conventionalised reasoning patterns, known as topoi. On this account the social meaning of a topos, as conveyed in a argument, is based on the set of idealogically-related topoi it indicates in context. We draw a connection between the role of personae in social meaning and the category adjustment effect, a well-known psychological phenomenon in which the representation of a stimulus is biased in the direction of the category in which it falls. Finally, we situate the interpretation of social signals as an update to the information state of an agent in a formal TTR model of dialogue.
2017
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Incrementality all the way up
Ellen Breitholtz
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Christine Howes
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Robin Cooper
Proceedings of the Computing Natural Language Inference Workshop