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1
SCiL 2022 Editors' Note
In: Proceedings of the Society for Computation in Linguistics (2022)
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2
Sorting through the noise: Testing robustness of information processing in pre-trained language models ...
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3
On the Interplay Between Fine-tuning and Composition in Transformers ...
Yu, Lang; Ettinger, Allyson. - : arXiv, 2021
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4
On the Interplay Between Fine-tuning and Composition in Transformers ...
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5
Pragmatic competence of pre-trained language models through the lens of discourse connectives ...
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6
Pragmatic competence of pre-trained language models through the lens of discourse connectives ...
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7
Preface: SCiL 2021 Editors' Note
In: Proceedings of the Society for Computation in Linguistics (2021)
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8
Exploring BERT's Sensitivity to Lexical Cues using Tests from Semantic Priming ...
Abstract: Models trained to estimate word probabilities in context have become ubiquitous in natural language processing. How do these models use lexical cues in context to inform their word probabilities? To answer this question, we present a case study analyzing the pre-trained BERT model with tests informed by semantic priming. Using English lexical stimuli that show priming in humans, we find that BERT too shows "priming," predicting a word with greater probability when the context includes a related word versus an unrelated one. This effect decreases as the amount of information provided by the context increases. Follow-up analysis shows BERT to be increasingly distracted by related prime words as context becomes more informative, assigning lower probabilities to related words. Our findings highlight the importance of considering contextual constraint effects when studying word prediction in these models, and highlight possible parallels with human processing. ... : Accepted for publication in Findings of ACL: EMNLP 2020 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2010.03010
https://dx.doi.org/10.48550/arxiv.2010.03010
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9
Assessing Phrasal Representation and Composition in Transformers ...
Yu, Lang; Ettinger, Allyson. - : arXiv, 2020
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10
Preface: SCiL 2020 Editors' Note
In: Proceedings of the Society for Computation in Linguistics (2020)
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11
What BERT Is Not: Lessons from a New Suite of Psycholinguistic Diagnostics for Language Models
In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 34-48 (2020) (2020)
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12
Mandarin utterance-final particle ba (吧) in the conversational scoreboard
In: Sinn und Bedeutung; Bd. 19 (2015): Proceedings of Sinn und Bedeutung 19; 232-251 ; Proceedings of Sinn und Bedeutung; Vol 19 (2015): Proceedings of Sinn und Bedeutung 19; 232-251 ; 2629-6055 (2019)
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13
Assessing Composition in Sentence Vector Representations ...
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14
Relating lexical and syntactic processes in language: Bridging research in humans and machines ...
Ettinger, Allyson. - : Digital Repository at the University of Maryland, 2018
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15
Relating lexical and syntactic processes in language: Bridging research in humans and machines
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16
Towards Linguistically Generalizable NLP Systems: A Workshop and Shared Task ...
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17
The role of morphology in phoneme prediction: Evidence from MEG
In: Brain & language. - Orlando, Fla. [u.a.] : Elsevier 129 (2014), 14-23
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18
Mandarin utterance-final particle ba in the conversational scoreboard
In: LSA Annual Meeting Extended Abstracts; Vol 4: LSA Annual Meeting Extended Abstracts 2013; 13:1-5 ; 2377-3367 (2013)
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