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1
Syntactic Persistence in Language Models: Priming as a Window into Abstract Language Representations ...
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2
Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts ...
Abstract: Dialogue participants often refer to entities or situations repeatedly within a conversation, which contributes to its cohesiveness. Subsequent references exploit the common ground accumulated by the interlocutors and hence have several interesting properties, namely, they tend to be shorter and reuse expressions that were effective in previous mentions. In this paper, we tackle the generation of first and subsequent references in visually grounded dialogue. We propose a generation model that produces referring utterances grounded in both the visual and the conversational context. To assess the referring effectiveness of its output, we also implement a reference resolution system. Our experiments and analyses show that the model produces better, more effective referring utterances than a model not grounded in the dialogue context, and generates subsequent references that exhibit linguistic patterns akin to humans. ... : In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020) ...
Keyword: Computation and Language cs.CL; Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2011.04554
https://arxiv.org/abs/2011.04554
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3
Analysing Lexical Semantic Change with Contextualised Word Representations ...
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4
Evaluating the Representational Hub of Language and Vision Models ...
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5
Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts ...
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6
You Shall Know a User by the Company It Keeps: Dynamic Representations for Social Media Users in NLP ...
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7
Psycholinguistics meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering ...
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8
Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat ...
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9
The Road to Success: Assessing the Fate of Linguistic Innovations in Online Communities ...
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10
Semantic Variation in Online Communities of Practice ...
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11
The LAMBADA dataset: Word prediction requiring a broad discourse context ...
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