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BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models ...
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Including Signed Languages in Natural Language Processing ...
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Including Signed Languages in Natural Language Processing ...
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Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? ...
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Measuring and Improving Consistency in Pretrained Language Models ...
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Aligning Faithful Interpretations with their Social Attribution ...
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Amnesic Probing: Behavioral Explanation With Amnesic Counterfactuals ...
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Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent ...
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Asking It All: Generating Contextualized Questions for any Semantic Role ...
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Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ...
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Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ...
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Ab Antiquo: Neural Proto-language Reconstruction ...
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Abstract:
Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.353/ Abstract: Historical linguists have identified regularities in the process of historic sound change. The comparative method utilizes those regularities to reconstruct proto-words based on observed forms in daughter languages. Can this process be efficiently automated? We address the task of proto-word reconstruction, in which the model is exposed to cognates in contemporary daughter languages, and has to predict the proto word in the ancestor language. We provide a novel dataset for this task, encompassing over 8,000 comparative entries, and show that neural sequence models outperform conventional methods applied to this task so far. Error analysis reveals variability in the ability of neural model to capture different phonological changes, correlating with the complexity of the changes. Analysis of learned embeddings reveals the models learn phonologically meaningful generalizations, corresponding to well-attested ...
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Keyword:
Artificial Intelligence; Computer Science and Engineering; Intelligent System; Natural Language Processing; Psycholinguistics
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URL: https://underline.io/lecture/19656-ab-antiquo-neural-proto-language-reconstruction https://dx.doi.org/10.48448/7cw5-e737
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Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora
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In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03161637 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States. pp.538-555, ⟨10.18653/v1/2020.acl-main.51⟩ (2020)
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