Papers by Arabella Sinclair
Construction Repetition Reduces Information Rate in Dialogue (2022.aacl-main)
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| Challenge: | We observe that construction usage lowers the information content of utterances. |
| Approach: | They propose to use construction repetition to mitigate information rate in English open-domain spoken dialogues. |
| Outcome: | The proposed method lowers the information content of utterances, while increasing the frequency and density of repetition. |
AnaLog: Testing Analytical and Deductive Logic Learnability in Language Models (2022.starsem-1)
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| Challenge: | Existing approaches to NLP tasks rely on pre-trained language models, but some do not. |
| Approach: | They propose a natural language inference task to test pre-trained language models for logical reasoning capabilities. |
| Outcome: | The proposed language model performs better than other models across logical connectives and reasoning domains, but is sensitive to lexical and syntactic variations in the realisation of logical statements. |
Surprisal Minimisation over Goal-directed Alternatives Predicts Production Choice in Dialogue (2026.acl-long)
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| Challenge: | a method to model utterance production is based on information-theoretic notions of cost . a technique to generate alternative sets of utterables is proposed . |
| Approach: | They propose a procedure to generate both types of alternative sets using language models. |
| Outcome: | The proposed procedure allows for speaker- and listener-oriented interpretations of different cost measures. |
Do Language Models Exhibit Human-like Structural Priming Effects? (2024.findings-acl)
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| Challenge: | a recent exposure to a structure facilitates processing of the same structure, a study finds . structural priming is well attested in humans, for both language production and comprehension . |
| Approach: | They use the structural priming paradigm to investigate where priming effects manifest . they find that rarer elements within a prime increase priming effect . |
| Outcome: | The findings provide an important piece in the puzzle of understanding how properties within their context affect structural prediction in language models. |
Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts (2020.emnlp-main)
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| Challenge: | Subsequent references exploit the common ground accumulated by the interlocutors and tend to be shorter and reuse expressions that were effective in previous mentions. |
| Approach: | They propose a model that generates first and subsequent references in visually grounded dialogue . they also implement a reference resolution system to assess the referring effectiveness . |
| Outcome: | The proposed model produces better, more effective referring utterances than one not grounded in the dialogue context. |
Structural Persistence in Language Models: Priming as a Window into Abstract Language Representations (2022.tacl-1)
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| Challenge: | a rich literature has emerged in the last few years addressing these questions, including whether specific LMs have acquired specific linguistic constructions. |
| Approach: | They introduce a novel metric and release Prime-LM, a large corpus where they control for various linguistic factors that interact with priming strength. |
| Outcome: | The proposed model can learn abstract structural information independent of the structure of a sentence and is able to perform tasks that require natural language understanding skills. |
Is Information Density Uniform in Task-Oriented Dialogues? (2021.emnlp-main)
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| Challenge: | Evidence for the uniform information density principle has been found at many levels of language production. |
| Approach: | They propose to use the Uniform Information Density principle to test whether and within which contextual units it holds in task-oriented dialogues. |
| Outcome: | The proposed method is able to reduce fluctuations in the density of the information transmitted. |